Episode 1

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Published on:

20th May 2026

How AECOM is Revolutionizing Reality Capture

Welcome to season 3 of the Confluence podcast! In this episode, AECOM’s Matthew Anderle joins Randall Stevens and Evan Troxel to break down how AECOM is pushing reality capture forward with custom-built robotics—rovers for “old dirty basements,” pipe crawlers for long culverts, and aquatic platforms for below-water inspections. They discuss layering environmental sensing on top of LiDAR point clouds, why digital twins must be operational (not just “great existing conditions models”), and what it means to help deliver LA28 as the first Olympics delivered in BIM.

This episode is a tour through AECOM’s “mobile autonomous reality capture” toolkit, purpose built to extend scanning into places people can’t (or shouldn’t) go.

They discuss:

  • Why AECOM built a robotics program for reality capture: safety, access, and repeatability in harsh/confined environments
  • “Sensorium” point clouds: humidity, temperature, air quality/particulates, and other context layered onto spatial data
  • Hardware + workflow highlights: wireless FPV, safety tethers, modular payloads, off-the-shelf tool batteries, and custom electronics
  • The “fiducial arm” problem: how to create registration targets inside smooth pipes so 500’ scans actually align
  • Makerspaces, trains, and hands-on fabrication as a pipeline for future STEM + AEC careers
  • LA 2028: transforming ~60 venues on an immovable deadline, and what it means to run the program’s common data environment

Links from the episode

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The Confluence podcast is a collaboration between TRXL and AVAIL, and is produced by TRXL Media.

Transcript
Randall Stevens:

Welcome to another Confluence podcast.

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I'm Randall Stevens, and as usual,

I have my sidekick, uh, Evan Troxel,

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or I'm his sidekick is probably the

reality of this, uh, was was at AU

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last week and had a lot of people, uh,

I had somebody, uh, we're like, we.

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They were standing there like, I know your

voice because I listened to that podcast

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Evan Troxel: Wow.

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Randall Stevens: I'm,

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Evan Troxel: Nice.

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I

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Randall Stevens: few

people listen, but, uh,

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Evan Troxel: excellent.

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Randall Stevens: a very

special guest with us today.

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He's kicking off our third season.

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It's Matt Anderle from, uh, AECOM.

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Um, Matt is.

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He's been at AECOM.

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Let him tell you more about

what his role is there.

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But I'll just tell the quick story

that when I first, and we've become

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friends, so over the last few years,

but when I first met, uh, Matt,

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like in 2016 probably, or 17, we had

started those building content summits.

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may have even been before

that 15 or 16 timeframe.

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And, uh.

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We're work, it was the early stages.

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We're working on avail.

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It's gonna be this content management,

you know, including Surf for Revit.

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And I was telling somebody this

story last week that, uh, I, I'd

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never met Matt and he's there at

this, uh, building content summit.

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So I walk up and introduce myself

and I was like, yo, here's, we're

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working on this, like content stuff.

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And he is like, yeah, I, I manage a

little content and, uh, around Revit.

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you know, I did, I wasn't, I

wasn't even really aware of AECOM.

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Right.

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Been spent most of my time kind

of in the architecture world.

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And, uh, that won't even name me.

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He is like, I'm like, yeah, how many,

uh, how many seats would you be good for?

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Oh, I manage about 15,000

seats of people with Revit.

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And I'm like, oh, wait a minute.

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Matthew Anderle: Just a couple.

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Mm-hmm.

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Randall Stevens: need to, need to know.

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But anyway, just kind of a funny story

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Evan Troxel: Yeah.

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Randall Stevens: Matt was like,

he's, he's, he's a smart guy, very

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humble, but, uh, he's done, he

does some really amazing stuff.

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So this is gonna be a fun conversation.

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Matt, why don't you just.

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Tell us a little bit more about what your

official role is, and then we'll dig in.

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Matthew Anderle: Oh, what else

could I add to that, Randall?

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That, that was a great introduction.

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Um, so the official title is Director of

Digital Strategy and, uh, I work with our,

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our teams all over the world to try to

advance, um, how we, uh, deliver advanced.

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Types of methodologies for

projects and, uh, extends all the

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way up into digital twins now.

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So, uh, we can officially put

that, officially put that as part

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of our repertoire and skillset.

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Um, in addition to that, um, always trying

to advance our practice and move forward.

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I run a robotics team and we use that

to compliment the tools that we use in

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an everyday basis for reality capture.

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So trying to advance

the, the needle forward.

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Been with AECOM for over 13 years now

and, uh, loved every minute of it.

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Evan Troxel: Can you just give

us kind of an, uh, an idea

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of where AECOM is currently?

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Because Randall gave the story

of, you know, 10 plus years ago.

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Where, where's, Where's that

gone in the last 10 years?

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Matthew Anderle: Well, so we've

evolved, of course, uh, we've, we've

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moved beyond the, we need to develop

better standards into, we need to

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deliver more intelligent models.

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And, uh, that really leads us

into that digital twin component.

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And I have a high bar for

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Evan Troxel: Hmm.

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Matthew Anderle: twins.

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Um, if anybody asks me, I'm gonna tell 'em

that it needs to be an operational model.

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It has to have

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Evan Troxel: Hmm.

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Matthew Anderle: into the field.

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Otherwise, it's just a really

great existing conditions

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model, right, which has value.

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But I think that digital

twin is an operational, um.

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Compliment to what we're already

using for the asset management world.

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Evan Troxel: Very cool.

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I.

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Randall Stevens: I, uh, I had said that

this season I wanted to do a couple,

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and Matt was the first, uh, this is the

first kind of Guinea Guinea pig episode

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where I wanted to do a crib style.

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So I actually went up.

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Matt, I'm in Kentucky in Lexington.

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Matt's about three and a half hour drive

north of me in Columbus, Ohio, and I've

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been up there a couple times before.

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He is got this great office and workshop.

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It's like, like going to Sam's workshop.

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To go up to, to Matt's place 'cause

he is building all the robotics.

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And we'll talk a little bit, but I did go

up and we shot some footage, which we're

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gonna integrate in, into this episode

as we talk about the different kinds of

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things that Matt and his team are doing.

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But, but part of it, his official

role at AECOM is they're building,

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Robots basically, that they can

send in for scanning and reality

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capture, um, of those kinds of things.

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So, we'll, uh, maybe Matt, you can start

there and we can, you know, we can dive

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backwards into, you know, from the Revit

side of things, but, um, maybe you can

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just talk about what you all are doing

on the robotic side and, uh, and then

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we'll, we'll lead this into how you,

you got there and some of your hobbies

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and what you're doing on that front.

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Matthew Anderle: Sure.

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Yeah, absolutely.

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a lot of what we've developed so far

has come outta the necessity, right?

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We've got these projects that, introduce

challenges to people in, in the

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environmental conditions that we would

be exposed to our, our risk factor.

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And, um, simply maneuvering 20 or 30

pounds worth of scanning equipment

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around some of these spaces is

of, uh, concern for our staff.

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And, and doing that in a very

hot and humid environment.

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And then, you know, trying to

navigate, uh, low clearances and other.

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Kind of obstructions like that,

uh, are, are just difficult, right?

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If you're doing that all day,

every day for a month or so, uh,

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it becomes taxing on our staff.

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And so, using some of my hobbies

and skill sets and experience in the

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past, um, some of the kind of micro

fabrication type of stuff that I do, it,

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uh, became evident that we could make

something that could improve our process.

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And in, so, uh, in doing so, we,

we developed these rovers that

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essentially are tow vehicles for

lidar scanning, uh, equipment.

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On top of that, we have sensors

that are built into them.

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So we get more information from that,

um, activity on site and can compare that

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now to, uh, the different spaces that we

scanned and, and bring some additional

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metrics back to our, our clients who

are asking it to, to get into these,

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uh, spaces and bring that kind of level

of information back that, um, otherwise

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wouldn't really be obtainable in any easy

mechanism, uh, for humans to, to approach.

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And we get to a point where.

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We're in scenarios like sub basements

of buildings that are 70 years old.

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And if you can imagine, uh, 70 years

ago we didn't have internet and

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we didn't have a lot of the, um,

kind of the power demands and other

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communication demands that we have now.

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So, uh, approaching a building

of that structure of that age.

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The sub basements are four feet tall.

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They have dirt floors, kind of

muddy floors at this point because

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of the, the environmental scenarios

that exist there and anywhere

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they could add new infrastructure.

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They ran it however they could run it.

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And so there's not a consideration

for serviceability or accessibility

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for, for humans in that space.

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It's just a very narrow and

tight space to begin with.

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And then you add a, a layer of

evolution in, in the ways that

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we use those buildings over time.

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Um, it adds a layer of complexity.

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So, um, in that scenario, one of the first

things that we observed is in some spaces

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there's 14 inches of clearance, and,

and that's between the mud and the pipe.

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And so, uh, to be able to maneuver

below that or around that, um,

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is a very complicated task.

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And, and.

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Doing that on top of carrying very highly

sensitive equipment like laser scanners,

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uh, would be almost unapproachable.

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So, uh, the robotics program really

spawned from the, the challenge in

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front of us, and it was something

that our teams had done in the past.

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It's not ideal, but it's something

that we could improve upon.

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And, uh, and as we looked at the

ways that we would, you know, capture

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the information, we also looked

at the ways that the rovers would.

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Um, would interact with

the devices itself.

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So carrying, you know, battery packs for

the devices, carrying communication with

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the devices, be able to, um, extend the

range of our, our human staff now, um, we

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could send rovers out into these, these

spaces to cover a hundred thousand square

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feet and then bring those back to where

we had our staff situated a safe location.

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And then at what we could also,

we could do, now we have a rover,

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right, that can move around.

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It's got a computer on board.

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We can collect a very high level of data

set that comes back with the lidar cloud.

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And, and as we stop and, and capture

positions, now we're capturing

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environmental, uh, considerations.

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So what kind of humidity is in that space?

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What kind of temperatures in that space?

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Uh, looking at, uh, if there's any dust

or particle kind of, uh, intrusion.

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So if there are any air qualities

that we need to be concerned about.

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Um, all of that now is a data layer

set that's on top of the point

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cloud, which is otherwise just.

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Data, right?

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And now when you pair those things

together, you start to look at

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what is the condition of this area?

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Do I have hotspots?

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Do I have very humid spots?

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And why?

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Is there a leak?

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Or is there steam?

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Is there things that are kind of being

absorbed into that, that, uh, location

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that shouldn't be there or could be

rectified so that there's a, a higher

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op, operating level of service that

comes through the, the building itself.

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um, and that evolved into, I think

we have seven different vehicles now.

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Working on our eighth and it's, uh, it's

everything from that kind of tow vehicle,

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high data collection rover up to, uh,

we've got like a pipe crawler that's

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really meant to go into a very small

diameter pipe and, and navigate through in

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a, in a singular direction, and then come

back and, and capture, um, high resolution

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video, spherical video, uh, the same

environmental considerations that we are.

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We're looking to collect and, um, and

go into areas that people don't fit,

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first of all, and then go into areas

where we have that high risk, where

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we're traveling a thousand feet down a

storm sewer, and the access points are,

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you know, 1500 feet or 2000 feet apart.

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Uh, in addition, we do some aquatic

vehicles, so we're looking at, um.

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scanning underneath, like

bridge, uh, structures.

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Looking at bait mates.

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We have cameras that go below water.

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We've got mathematics sensors that will

go down and actually scan the terrain.

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So we have, uh, now a capacity to

bring a vehicle into a situation where

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we're traveling up and down through

a river or under structures that, uh,

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would be hard to get, uh, you know,

a human being into, and we could do

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so remotely, safely from the shore.

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we try to introduce the same kinds of

data collection that we have in our

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rovers within any of our vehicles.

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as we're trying to travel through the,

the water and, and get into the spaces,

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we can actually kinda track current and

how far, you know, how fast we're moving

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and, and how far we've gone, where we

might find those kind of subsurface,

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uh, obstructions or other kind of, um,

uh, debris or, or elements of awareness

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that, that we should know about.

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And, um.

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Water temperatures and air temperatures

and, and try to kind of discover

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what kinds of things are happening

around the scenarios that we're,

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we're doing this inspection.

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Evan Troxel: That's pretty fascinating

because I think about photography

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being like a moment in time, right?

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You, you see a photograph, it could

be the absolute perfect conditions.

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But just, just by what it looks like.

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You're actually talking about

painting the whole picture.

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And I, I can't tell you how many times

I've taken a photograph and I'm like, no.

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People who look at this have no

idea how hot it is or how windy it

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is, or how cold it is, or what it

smells like, or any of those things.

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And I think it's absolutely fascinating

that you're trying to paint a picture

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of like, you're not just capturing the

built environment into a point cloud.

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You're trying to capture

these additional layers.

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I think that's just super cool.

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It's like.

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Because like you said, like there's

mud down there, so there's humidity

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or there's moisture intrusion or

whatever, and you start to get a bigger

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sense of what's actually going on in

these locations that, like you said,

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it's difficult to stick a person in

there, let alone for how much coverage

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you're talking about and for the time

period it would take to scan all that.

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I think it's, it's pretty cool.

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Could you kinda give us an idea of.

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Uh, just paint a picture of what

these, for those who aren't gonna

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get to see Randall's shots of these

robots, like on the video, who, for

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the listeners out there, can you just

kind of explain what these rovers

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kind of look like, what size they are?

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I know you've got several of them, but.

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Matthew Anderle: Sure.

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Uh, they range from anything that is

about, uh, eight inches in diameter.

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And we have a little trike that has

like a, a center articulated frame, so

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we can turn it on a center pivot and,

and maneuver in a very tight space,

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um, in a circle that's almost, uh.

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say 10 inches in diameter.

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But that allows us to go into anything

like an eight inch diameter pipe,

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or in some cases we have, uh, these

narrow, uh, kind of channels of, of

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infrastructure like conduit piping

and, and communication cables that go

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through a, a hole in the wall, literally.

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That travels the entire

building or half the building.

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And so we've taken our trike and we've

ran it a couple hundred feet with, you

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know, high resolution video to observe

where these conduit runs actually

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progress through that space and where they

introduce and, and then leave in that,

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in those same kind of, uh, scenarios.

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Uh, anything from that size.

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So, so a very small vehicle up

to our largest, which is about.

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It's, uh, 36 inches by three six

inches and has a capability to raise

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itself and lower itself to, uh, carry

a scanner on top of its back and, and

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really maneuver through a space and,

and get to the lowest point it possibly

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can while still moving a scanner.

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And then, um, kind of navigate over debris

or obstacles that are in front of it.

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Um, our go-to though is our, um, our.

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we call Scout and it's about a,

the size of a pizza box and it's

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got, you know, very large kind of

ba balloony paddle tires on it.

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So when we get to that muddy

scenario, we can dig in and,

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and maneuver through that space.

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It's also when we have our tow package

on where we can add extra batteries

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outta those lighter scanners to it.

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And, um, and it is the most versatile

'cause we can take it the storm

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sewers, we can take it into muddy

basements, we can take it into fields

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and, and use it, uh, kind of likewise

across all those different scenarios.

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Uh, same with our, our aquatic.

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So our, our aquatic platforms also are

about the size of a pizza box up to about

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36 inches by three six inches a square.

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And we'd use like a dual pontoon

scenario where we're, uh, we've got a

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couple different drive mechanisms, so

differential drive within two props.

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And then in the center we have, uh,

an array of, of frameworks that we can

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attach all kinds of different sensors to.

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our goal is really in this whole, um,

platform we call Markup, which stands for

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mobile, uh, mobility, mobile Autonomous

Reality Capture, utility Platform.

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Uh, our whole goal here is to be

versatile, and so we use this, uh,

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kind of structural, uh, framing

mechanism to, to be able to

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slide in and arrange and, and to.

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Change or augment those vehicles

to address any kind of scenarios

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that we're gonna go into.

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One of the jokes that we have is

we'd like to deploy our rover with

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the same configuration twice, right?

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And we get to all these different

locations and, and different types of,

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uh, of activities that we have in the

field that we have to mount more sensors.

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We've attached double cameras, three

cameras, uh, different types of sensors,

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different lighting packages to it.

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Uh, to be able to get the, the best

results possible within, you know, a an

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ever changing kind of, uh, infrastructure

environment We have to approach.

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Randall Stevens: you brought one

of those platforms to Confluence a

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couple years ago and showed it off.

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Was it the.

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Matthew Anderle: I did that was scout.

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Yep.

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Randall Stevens: Yeah, that was it.

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That was the size.

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Yeah.

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I was just gonna comment, a

couple of things that struck me.

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One, you do tether.

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that if, if, you know, 'cause

you're sending this thing

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off into the, in, into the

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Matthew Anderle: Hmm.

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Randall Stevens: underneath these

buildings, but you do, uh, have a safety

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tether so that if it ever gets stuck

or something, you can pull it back out.

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I thought that was interesting.

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A cable.

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How far, how far can you reach remotely

or how, how far off can these devices

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Matthew Anderle: a good question.

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So our tether iss not traditional.

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most of these, uh, companies you

see, they're doing inspection

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with rovers are, uh, communication

tether and power tethers.

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Um, ours is strictly for safety and,

um, and if everything on our rover's

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battery operated, everything is

remote controlled, uh, wirelessly.

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So we're, we're.

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Commanding things on the rover and

it's, it's taking action from what our,

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our, uh, wireless commands are sending.

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theoretically our, our equipment

can go up to a mile plus and, uh,

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it's something that we've never had

to challenge yet, but we've kind of

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tested out to a good plus thousand

feet range and, and had full control.

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So it's, it's, uh, certainly capable

of extending beyond, um, what our.

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Our challenges have been on projects in

the sites, uh, the uniqueness is if we had

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to disconnect the tether, uh, we could,

so we could actually run the rover all

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the way through, let's say a storm sewer,

collect it at the other end and bring

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it up through and, or, or reconnect and

then continue down, um, even further.

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But, uh, we're completely wireless,

if we had to, we could dis disconnect

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the, the tether altogether and

just run it completely remote all

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the way through an environment.

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Evan Troxel: So is it streaming

video back to you the whole time?

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So I would imagine you kind of need

to see what it's seeing at some level.

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Matthew Anderle: Absolutely.

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So we have, uh, long range, uh, first

person view cameras like you'd have

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on drones and we have screens that

we watch, but we can put goggles

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on and watch that way as well.

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And, uh, through a gimbal.

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So we have a kind of a, a camera on the

front that uses a gimbal to look around,

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uh, gives us full optics on where we

are in the, in the scenario within that.

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Environment and, uh, can use it

to drive forward or turn around

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and drive backwards with it.

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So it gives us a lot of versatility of,

of understanding where we are in the,

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in the position with this remotely.

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Um, but in addition to that, we have

cameras that are capturing, um, eight K

344

:

resolution, 360 video at the same time.

345

:

And, uh, we compare that with the data.

346

:

We compare that with the point clouds.

347

:

So, uh, a lot of sensors that

are, are built into this, become

348

:

a sensorium information, and

it's something that, uh, we're.

349

:

In a mission, we're trying to really

collect as much as possible and then use

350

:

that as a a means to kind of evaluate

visually or translate that into, um,

351

:

any type of actions that have to happen

within the, the client's expectations

352

:

or, or with the scenarios on site.

353

:

Randall Stevens: One of the things,

Evan, that I thought was really cool,

354

:

maybe maybe other people do this,

but Matt's designed these with, uh,

355

:

the battery packs are like standard

batteries that you would use, like

356

:

a DeWalt or a, you know, on a, on a.

357

:

Evan Troxel: Oh, okay.

358

:

Randall Stevens: it's like,

you know, he was telling.

359

:

Evan Troxel: Cordless tool batteries.

360

:

Yeah.

361

:

Randall Stevens: if we're out and

we need an extra battery right, or

362

:

something, you know, need a part,

you can just run down to the hardware

363

:

store and grab extra batteries.

364

:

So thought

365

:

Evan Troxel: Very cool.

366

:

Randall Stevens: uh, pretty,

pretty smart, uh, of you.

367

:

The other thing I was gonna say when you

were talking about the links, um, and

368

:

I'm pretty sure we've got some footage

here that we'll be able to show of

369

:

this, but they've, uh, created a arm.

370

:

That can be attached to the rover

and it will actually take fiducials

371

:

that are on a magnet and stick 'em

to the, to the pipe above so that

372

:

they can then go further, and then

they can use that for calibrating,

373

:

you know, across longer, longer

374

:

Evan Troxel: okay.

375

:

Randall Stevens: So.

376

:

Evan Troxel: Like a registration point?

377

:

Yeah.

378

:

Okay.

379

:

Randall Stevens: they've actually

created the, you know, the fiducials

380

:

with the magnet on it, and the arm will

get one off the end of it and stick

381

:

it on as it goes down its mission.

382

:

So it's pretty cool.

383

:

Matthew Anderle: And that was a challenge

because we had this project to, um, scan

384

:

a culvert to determine if there's any

sort of, uh, kind of soil penetration

385

:

or deform deformation of that pipe.

386

:

Over time, which we actually did

discover some, uh, within our scans,

387

:

but to laser a scan a smooth pipe,

you have no registration points.

388

:

And so we went 500 feet, uh, down two of

these that were parallel to each other.

389

:

And because there was no registration

points, we made this, uh, it's four

390

:

axis mechanical arm to take these

targets off of a carriage and lift

391

:

them up and ly connect them to the

top of this, um, this steel pipe.

392

:

after we did that mission, came

back, dropped off the arm, put on

393

:

the scanner, and then went through

and scanned the 500 feet and had,

394

:

uh, say perfect registration, but we

had registration points throughout

395

:

the entire pipe from start to finish

and then targets on other ends.

396

:

So we can use that for referencing.

397

:

Randall Stevens: how would this have

been accomplished before you, you

398

:

know, had these devices that you've

built, how, how would, would, was

399

:

it possible to do more expensive?

400

:

Are you cutting time?

401

:

Are you

402

:

Matthew Anderle: The biggest thing

is mitigating risk to our staff.

403

:

And um, you could have somebody who's

confined space trained who's crawling

404

:

through these pipes, likely on, you know,

hands and knees kind of approach, right.

405

:

And have some sort of surface

to sit on 'cause there's water

406

:

running through them, of course.

407

:

And then setting up tripods

over and over and over again and

408

:

trying to mark targets themselves.

409

:

So they'd have to navigate through

and actually set targets and then go

410

:

through again with a scanner to scan the.

411

:

The, uh, infrastructure with the rovers,

you know, we can sit back at the opening

412

:

of that area, these through with the

video feedback, and, and while we're

413

:

doing this, we're also getting the,

the video capture, set the targets,

414

:

come back, run the scanners, and then

go back to the, the office and, and

415

:

have a data package collected safely

and, and more, um, extensively than

416

:

somebody could, as a, as a person.

417

:

Randall Stevens: And I think you were

telling me about a project, maybe it

418

:

was earlier this year where you all were

old, old hospital, if I remember right.

419

:

In the

420

:

Matthew Anderle: Yeah,

421

:

Randall Stevens: And you all were

422

:

Matthew Anderle: the odbs, right?

423

:

The old dirty basements.

424

:

Randall Stevens: Yeah, confined

spaces, lots of, you know,

425

:

everybody's been in those steam

426

:

Matthew Anderle: Yep.

427

:

Randall Stevens: you know,

humid, terrible conditions.

428

:

And for you all to be able to, uh,

deploy these and, and get the data

429

:

you needed, uh, uh, for planning.

430

:

So yeah, there's probably, obviously

more and more buildings like that, that

431

:

need, uh, need these kind of, can use

these kind of capabilities to help scan,

432

:

Matthew Anderle: uncomfortable conditions.

433

:

Randall Stevens: Yeah, No, I'm

434

:

Matthew Anderle: Yeah.

435

:

Randall Stevens: I wanna be sitting out

there with a, uh, remote control and,

436

:

Matthew Anderle: Yeah,

437

:

Randall Stevens: and sit out there

where it's a little more comfortable

438

:

Matthew Anderle: very true.

439

:

Randall Stevens: data in.

440

:

let's talk a little bit about, um, how

you got into building the robotics.

441

:

So, you know, I was telling Evan earlier,

it's like when you go up to your shop,

442

:

it's like going to Santa's workshop.

443

:

Uh, you've got, you know, 3D

printing capabilities, but,

444

:

Matthew Anderle: Yeah.

445

:

Randall Stevens: uh.

446

:

Tell us about your hobbies and

how that led to your being able

447

:

to tie that into your profession.

448

:

Matthew Anderle: Yeah, absolutely.

449

:

So I've been into, um.

450

:

Just models for my entire life, right?

451

:

All the way from kids up till now.

452

:

There's no difference, as my interest

has grown, so as my, my use or, or, um.

453

:

Pursuits of those different

hobbies has, has evolved.

454

:

Uh, 3D printing's opened a lot

of stuff for us, you know, and if

455

:

you're a, a mic, I call it micro

manufacturing, but if you're a, a

456

:

rapid prototyper, micro manufacturing,

you know, enthusiast, you're gonna

457

:

have 3D printers and make stuff.

458

:

And the first thing you make

is, I need a fix for apart.

459

:

Right?

460

:

And I broke something in my

house, I could 3D printed now.

461

:

Um.

462

:

Randall Stevens: Okay.

463

:

Matthew Anderle: Applying that to rc,

you know, and, and cars and trucks

464

:

and boats and planes, you name it.

465

:

Um, you start to modify, right?

466

:

Not create custom parts.

467

:

And that eventually evolves into, I pitch.

468

:

You could just build a brand new

thing and, and start from scratch.

469

:

So, um, all of our design software

kind of yields to the creative and,

470

:

and whether you're making buildings,

you're making parts, um, it's all

471

:

that, um, kind of inspired process way

to, to make something out of nothing.

472

:

uh.

473

:

And then I got into robotics.

474

:

So I, I took computer programming

as a minor in, in college and,

475

:

uh, now I'm pairing, making stuff

with programming stuff and, and

476

:

it does stuff when I'm done.

477

:

So that, uh, that's really how kind of

robotics has been introduced into, into

478

:

my passion and, and now as part of my job.

479

:

Randall Stevens: When you're building

the robots that you're using, uh, uh,

480

:

of the, uh, DPT team, are you, are you

making everything including the software?

481

:

How much of it's already gave away

that the batteries, you're going to

482

:

buying those, but almost everything

else you're actually building yourself?

483

:

Is that

484

:

Matthew Anderle: So, so the frames, the

tires, um, anything that's a product of,

485

:

uh, of other interests in the industry,

um, is something that we would purchase.

486

:

But, um, all the customization, so

anything that, uh, is unique outside

487

:

of extruded aluminum wheels and

motors, um, all of that is something

488

:

that we self-develop and, uh, even

gone as far as developing our own

489

:

circuit boards to run these machines.

490

:

Uh, we still have microcontrollers

that are available like Arduinos and

491

:

PI and things like that, but, um.

492

:

We plug those into our own circuitry

components that actually control the

493

:

rovers and, and give us some instruction,

uh, forward and backwards through that.

494

:

It, um, it's unique in that, uh, we

have a lot of control and there's a

495

:

lot of burden in, in trying to do that

yourself without discovery, right?

496

:

We're trying to discover things,

um, how to do them better or how

497

:

to, to improve the efficiencies

of, of what that device is, is, um.

498

:

Kind of receiving processing

and, and how it's performing.

499

:

um, it's rewarding that, that we

can make any kind of augmentation

500

:

that we need almost instantly.

501

:

we need to program in new sensors and new

controls, new data collection, we can,

502

:

uh, usually turn that around within, you

know, a few hours, a few days, instead

503

:

of trying to find a solution, introduce

that, and then try to plug that in.

504

:

Evan Troxel: I, I'm curious, like on the

robotics side of things, have you gone

505

:

as far as finding robotics specialists

to bring into roles inside of AECOM like

506

:

architecture firms, you know, 10, 15 years

ago didn't have a data analysts, right?

507

:

They didn't have, yeah.

508

:

They didn't have developers

developing software, for example.

509

:

I mean, and now we're hearing

about like the, the work that

510

:

you're doing with robotics.

511

:

Is that something that you hire

specifically for in the business

512

:

or is this something that you've

just completely taken on yourself

513

:

and because of your, you.

514

:

Matthew Anderle: we've had, um, a couple

team members in our group that are, are

515

:

passionate about this industry like I am.

516

:

So we've, we've actually hired in

some of the traits that we've hired

517

:

are people who are, are really in

tuned with this kind of, uh, kind of

518

:

hobby, the, the RC hobby or the, the

micro manufacturing side of things.

519

:

Um, our latest.

520

:

You know, hire is, is somebody who's done

CNC and welding and, and those kind of

521

:

traits outside of their passion for bim.

522

:

And so that kind of skillset of, of

that person being an artist and, and

523

:

having that kind of, um, just passion

outside of work and, and being, you know,

524

:

involved with that on a regular basis.

525

:

They bring those skill sets to the team.

526

:

Um,

527

:

Evan Troxel: Yeah.

528

:

Matthew Anderle: team, I can

arguably say is, is somebody who's

529

:

either passionate about the design

side, the fabrication side, the

530

:

programming side, or the operator side.

531

:

And, and all of us are, are either like a,

a part 1 0 7 pilot or a pilot in the, in

532

:

the rover world because they've, you know,

been in RC or, or somebody who's more on

533

:

the aquatic side, does boating regularly.

534

:

So, you know, can kind of help navigate

currents and, and drive our aquatic

535

:

vehicles in, in different scenarios.

536

:

All of those have,

537

:

Randall Stevens: Perfect.

538

:

Matthew Anderle: skills that, that apply

into just the task of, of reality capture.

539

:

And, um, I hate to diminish

what we're doing, but they're,

540

:

they're tools for us, right?

541

:

They're just like a lidar scanner.

542

:

Uh, we use this to go and collect

data and come back, and that's, uh,

543

:

something that extends our services.

544

:

So, uh, Randall, you mentioned

DPT, stands for Digital

545

:

Practice and Technology, right?

546

:

It's a, a subgroup within AECOM that

is kind that high level delivery team.

547

:

to kind of advance BIM and SIM

and asset management, but we're

548

:

also on the reality capture side.

549

:

And so our rovers become these tools

that extend our capabilities into

550

:

places where either people can't go

or shouldn't go or don't want to go.

551

:

And um, and so we're also.

552

:

to evolve our team and grow our team

in that same capacity where, um, even

553

:

this last summer we had two interns.

554

:

One is a mechanical engineer who is

participating in some of the engineering

555

:

design and, um, and we're looking at a, a

new candidate for, uh, an apprenticeship

556

:

that is also in robotics and can

complement the team for programming.

557

:

Evan Troxel: Can you talk about tools

that have kind of evolved in this?

558

:

Realm for you over the last 10

years because it, it, I've seen some

559

:

incredible stuff from like Disney.

560

:

You, you see the, the swinging Spider-Man

that lets go of the, the web and does

561

:

back flips and stuff, and then there's,

they've even shown off stuff at their

562

:

conferences that they've been working on.

563

:

I, I assume, you know, obviously

advances also have to do with the

564

:

tooling, not just kind of like the

iterative process of building robotics

565

:

and testing and seeing what happens.

566

:

But I would imagine AI, for example,

with coding and things like that,

567

:

has kind of changed the game when

it comes to what you guys have.

568

:

Found your capabilities to,

to, to be able to pull off.

569

:

So like what else has in that

realm, has really helped open

570

:

this up in a bigger way than you

probably ever thought was possible.

571

:

Matthew Anderle: I think every aspect

of it from start of design, right?

572

:

Our tools that we have for, um,

analysis of design, uh, doing some

573

:

physics and load testing, generative.

574

:

Design in that, that respect, um,

helps us to better stand before

575

:

we actually fabricate something.

576

:

And

577

:

Evan Troxel: Mm.

578

:

Matthew Anderle: um, as we get into

fabrication, all the tools that

579

:

build stuff now are better, right?

580

:

We have more precise CNC machines

that are more approachable.

581

:

Uh, we've got faster printers,

like 10 times faster printers,

582

:

which, uh, is immense.

583

:

When you we're talking about a part

that takes 36 hours to print versus.

584

:

Seven or eight hours to print.

585

:

And so, um, our kind of, our design

source to, to introduction into

586

:

our rovers now is something that we

could do in a day instead of a week.

587

:

And so just being able to rapid prototype

something, test it out, you know, work

588

:

on, uh, the, the effects of that within

the Rover platform and how it improves or,

589

:

or challenges the, the rover essentially

is something that we can be more

590

:

immediate about and, um, and turn around.

591

:

Kinda designs and augmentations faster.

592

:

in the same regard, we couldn't process

all this data without ai, right?

593

:

We have to use, um, a, a very high

level of computation to be able

594

:

to just read point clouds and, and

process those, uh, uh, let alone from

595

:

the dataset that we're collecting

about the environment on top of it.

596

:

And, and we infuse those together.

597

:

So what we're trying to do is, is bring

that environmental information into the

598

:

cloud and understand, and, and I mean,

point cloud, bring those things together

599

:

so that you understand this kind of wealth

of information every time that we stop.

600

:

Grab a position's information and,

and capture what exists there.

601

:

So, uh, the tools to build what we make

and, and the, the things that we use to

602

:

program and evaluate the data, and then

the scanners themselves are, are more

603

:

efficient and, and higher resolution.

604

:

And they're getting smaller.

605

:

Right?

606

:

The.

607

:

The new, uh,

608

:

Evan Troxel: Hmm.

609

:

Mm-hmm.

610

:

Matthew Anderle: are starting to achieve

the same resolution that we had 10 years

611

:

ago and something that was 10 times the

size and, and now we can put that on

612

:

top of a rover and be able to get into

smaller spaces with a scanner and be more

613

:

versatile, run longer, um, go further and,

uh, still get, uh, similar data setback.

614

:

Randall Stevens: How much of the

materials changing, Matt, with what

615

:

you're able to, to, to print are,

616

:

Matthew Anderle: a lot of

advancements in materials.

617

:

Yeah.

618

:

Uh, these printers now can have carbon

fiber infused plastics and, and polymers.

619

:

Uh, that's something that didn't

exist in the industry, you know, five

620

:

years ago, maybe even three years ago.

621

:

So, um.

622

:

Randall Stevens: You get smaller

and smaller, stronger and

623

:

stronger, and smaller and smaller.

624

:

Matthew Anderle: Exactly, and, and

you're getting more of that professional,

625

:

um, industry engineering application

of, of material in your printer head.

626

:

And it's something that you can actually

build a part that's actually structurally

627

:

sound comparable to something if you CNC'd

or, or created out of another material,

628

:

um, that, that used a longer, much

more, uh, enduring kind of application.

629

:

So.

630

:

The, the printers itself, you know, the,

the higher resolution or the higher heat

631

:

outputs, the, the materiality of that,

that, uh, filament or if we're using

632

:

resin, the resin material that we have.

633

:

Um, all of those are, are

advancing technologies that, uh,

634

:

help our types of industries.

635

:

Let us build two things, and it

doesn't cost us a million dollars.

636

:

Randall Stevens: Evan, you're gonna

see in some of these images and

637

:

photos I took, but when, know, we

probably all had some R something.

638

:

Rc, when Matt says he's into rc, got

to, it is planes, trains, automobiles.

639

:

Dozens,

640

:

Matthew Anderle: It

641

:

Evan Troxel: Nice.

642

:

Randall Stevens: The model

train collections them

643

:

just alone are incredible.

644

:

Matt, what, uh, what are the

different scales of, uh, of, of train,

645

:

Matthew Anderle: So I'm, I'm

almost exclusively in scale,

646

:

Randall Stevens: it's

647

:

Matthew Anderle: is like the

one to one 60 range, right?

648

:

Randall Stevens: cool because, um,

you know, he's obviously got the,

649

:

the trains themselves, but he's

building the dioramas and the, uh,

650

:

Matthew Anderle: Mm-hmm.

651

:

Randall Stevens: module size, uh, so

as part of the club you can like build

652

:

these and then bring other people.

653

:

Everybody can bring 'em together

and that's how you build.

654

:

So maybe Matt, you can give a plug for

the 'cause I'm gonna go down to chat.

655

:

Is it Chattanooga the next summer?

656

:

Matthew Anderle: Chattanooga.

657

:

Yeah.

658

:

Randall Stevens: Yeah,

659

:

Matthew Anderle: The

NMRA convention in 26.

660

:

Yeah.

661

:

Randall Stevens: end up with a

bunch of people, uh, descending

662

:

on Chattanooga next summer for

663

:

Matthew Anderle: I.

664

:

It may be right if this is a

shout out for anybody, right?

665

:

Go down to Chattanooga next summer.

666

:

Um, end of July, early August, I

think is the, uh, the convention.

667

:

But, uh, they're, they're gonna set a

world record, which, uh, is something

668

:

that's not a small feat, and it's,

uh, using a standard called T Track.

669

:

And these are a module that's about

12 inches across and 14 inches deep.

670

:

That's the standard box.

671

:

You put two tracks on the front.

672

:

Then the rest of it is to

your inspiration and design.

673

:

And, uh, as long as you have the standard

set, you can snap any number of them

674

:

together and it makes, uh, a large layout.

675

:

So down in Chattanooga, they're

gonna set a world record for, uh, the

676

:

number of modules that are connected

together to make a, a layout, which

677

:

is, I forget how many miles of

length that that track's gonna be.

678

:

But, um, it's a, it's

an unprecedented event.

679

:

And, um, I have my own modules

that are going down there and,

680

:

and gonna participate myself.

681

:

Randall Stevens: As well

682

:

Matthew Anderle: Um.

683

:

Randall Stevens: uh,

Matt was showing me that.

684

:

you know, the controllers

for the, uh, for the trains.

685

:

got a couple of kits that he's kind

of built one smaller for testing.

686

:

You know, if you've

687

:

Matthew Anderle: Mm-hmm.

688

:

Randall Stevens: locomotive and you

can test it to make sure that it's

689

:

all set right before he, but he

is building, he's got larger with.

690

:

that open up, that can control like

what, 50 50 locomotives at a time.

691

:

So anyway, he's got a lot of really

cool electronics and equipment

692

:

that are used to, to do these

very large, massive train layouts.

693

:

Matthew Anderle: And uniquely

yet similar, uh, trains now

694

:

are controlled by computers.

695

:

And so if you're, if you've been out

of the hobby for long enough, uh, the

696

:

old, uh, dial throttle that makes your

train go forward faster, um, is still.

697

:

Available.

698

:

Right.

699

:

And, and some people still use that,

but, uh, for anybody in the, the

700

:

kind of the modern era of this hobby,

they're, it's all computer based

701

:

and it's all, uh, kind of floating

ground signals over the tracks and it

702

:

tells the computer chips what to do.

703

:

So every locomotive has a computer inside.

704

:

And, uh, and it reads the, the

signal that's like a layer.

705

:

If you ever did like ethernet over

your power lines, uh, it's the same

706

:

Evan Troxel: Mm-hmm.

707

:

Matthew Anderle: where it's

sending signals through

708

:

the track and then the, the

709

:

Evan Troxel: Wow.

710

:

Matthew Anderle: that and then

determine if it's instruction

711

:

for them or something else.

712

:

And if it's for them, then they take

action on what the instruction is.

713

:

So you can have trains running

in different directions.

714

:

You can have 10 trains on

the same track, all running.

715

:

At different speeds of each other.

716

:

But, uh, it's a, it's a, it's really

a, a data network over the track and,

717

:

and your locomotives are just, uh,

one of the devices that sit on it.

718

:

Evan Troxel: It's interesting to think

about kind of the crossover, even just

719

:

with what I know about media and like,

well, people who put together shows

720

:

that go on network tv, for example.

721

:

Like, like an NFL game or something.

722

:

It's all, it's.

723

:

It's a, they use a system called EVS.

724

:

Right.

725

:

And it's just a playout, it's an

order of events that happen over time.

726

:

And I could imagine you having

like a, a grand kind of playbook of

727

:

everything that's gonna happen and,

and it's sending those signals out.

728

:

And like you said, some are

picking up on 'em and some are just

729

:

saying that that ones not for me.

730

:

But then it executes it at the right time

in the right order and you can orchestrate

731

:

like this whole thing to happen.

732

:

That's, that sounds amazing.

733

:

Matthew Anderle: We even built

sensors into our modules too.

734

:

So as trains approach, you know.

735

:

Crossing gates will go down

or switches will, will throw,

736

:

Evan Troxel: Like behaviors

automatically happen.

737

:

Yeah.

738

:

Matthew Anderle: it's based

739

:

Evan Troxel: Yeah.

740

:

Very cool.

741

:

Matthew Anderle: you can have it based

on what locomotive's approaching even.

742

:

Right.

743

:

And have it, if it's, if it's

this locomotive, you know, throw

744

:

this turnout and go into this

stall or something like that.

745

:

it, uh, it's,

746

:

Randall Stevens: Matt, that you were

showing that your club, you know,

747

:

they get kids involved too, so that

748

:

Matthew Anderle: mm-hmm.

749

:

Randall Stevens: they can

do, you know, they can let.

750

:

Kids learn, you know, and build,

build their own part of their module.

751

:

Each of 'em gets their own

module to put in there.

752

:

So I think it's just a great,

great that you can bring young

753

:

people, you know, into that hobby,

754

:

Matthew Anderle: Yeah.

755

:

Randall Stevens: translates into

these great careers like what Matt's

756

:

built for himself at AECOM, uh, with,

with these kinds of technologies.

757

:

So what a great gateway to, uh,

getting more people involved.

758

:

Matthew Anderle: Specifically

about trains alone.

759

:

Um, I've ran fusion classes

on how to model things.

760

:

I run, um, landscaping classes, assembly

classes, kinda that craftsmanship level.

761

:

Um, talking about trains,

talking about scale, right?

762

:

You introduce kids to scale and

what that means as far as sizing

763

:

things from the real world down

to the size of a module, right?

764

:

And, um, and any of those become

a passion for someone, right?

765

:

You could be, um, somebody

who wants to get into art.

766

:

Because of the way you're painting or

you're, you know, creating landscapes

767

:

or, or generating that kind of

design on, on the module itself.

768

:

Or if you're, um, somebody who's more

of the engineering, you want everything

769

:

to be perfect and, and build things

to scale and, and fabricate, or.

770

:

you want to get into trains and

transportation and any kind of

771

:

kind of market sector that leads

along the lines of, of how we

772

:

maneuver through our environment.

773

:

You know, get into autonomous

vehicles, you can get into, you

774

:

know, the way we kind of automate

transport and, and when we get into

775

:

this AI driven environment around us.

776

:

Um, all of those things

start with some inspiration.

777

:

And in our club is pretty good at

the outreach to, know, conduct, um.

778

:

Some of these workshops with like

boy Scout clubs or with, uh, youth

779

:

groups or schools, uh, and get in

front of them in that capacity.

780

:

And if the kids show interest, we'll

have 10 workshops, you know, as many

781

:

as they will allow us to participate.

782

:

Uh, our, our, our group is, is pretty open

to doing so and, and everything from the,

783

:

the software side to the, how do I things

and make things at scale and build stuff.

784

:

Evan Troxel: I was just wondering

if you could talk about that

785

:

aspect of it versus like schools

getting rid of programs like that.

786

:

Because another big thing that's

happened we've seen over the last 10,

787

:

15 years is makerspaces have popped

up where they have a lot of these

788

:

tools and it doesn't make sense for

everybody to own all these tools.

789

:

It makes sense for like a community

to own these tools that people

790

:

then get to use, but also, like

I said, like those programs have.

791

:

Uh, kind of disappeared from

the typical education system.

792

:

I would imagine that there's a huge draw,

you know, alone just because of that.

793

:

Matthew Anderle: There is.

794

:

And um, printers are approachable, right?

795

:

You can get them at local

stores here at least.

796

:

Um, everybody knows how to to use

them or how to get started with them.

797

:

So, um, what we've done is,

is try to create kinda these

798

:

curriculums that are, um.

799

:

Inspiring for the kids to,

to create something that they

800

:

could finish in a workshop.

801

:

maybe even start to 3D print or 3D

print and have ready, uh, by the next

802

:

time that workshop, uh, continues.

803

:

And, uh, if we find that if we have

something that turns into a tangible

804

:

object or turns into a result, uh.

805

:

Really kind of kick starts it and

then it, the, the pressure is to

806

:

hold back right now that you've

got started, how do we slow down?

807

:

But, uh, I, I think that you're right.

808

:

There's some things that, um, some schools

have those opportunities and others don't.

809

:

Um, my family and, and my nephews

and nieces have been in a, a school

810

:

where they've had robotics programs

in school, and, uh, so they have.

811

:

Rapid prototyping.

812

:

They have design, they have

that engineering component.

813

:

Um, others I know don't

necessarily have all those things.

814

:

So wherever we can, you know, find

that outreach and in our industry, it's

815

:

important to bring this skillset forward.

816

:

Right?

817

:

STEM is probably one of the greatest

things that have happened in

818

:

America and, and around the world.

819

:

for us to participate at any scale is

really helpful for us because that leads

820

:

to, you know, more people in the design,

engineering, and fabrication industry.

821

:

And, um, and helps kind of support

where we're growing as well.

822

:

And, and as a company, we're seeing

that coming out of school too.

823

:

So, uh, you know, individuals that we're

hiring for internships are coming outta

824

:

high school or coming outta college

that have, uh, that kind of experience

825

:

throughout their career, um, in education

and something that can apply to our teams.

826

:

Evan Troxel: Sign me up.

827

:

Randall Stevens: yeah, I know.

828

:

Sounds like fun.

829

:

uh, we'll put some pictures and video

up, but to describe, 'cause one of

830

:

the things he had built when we were,

when you started talking about scale,

831

:

you built a turbine that was a.

832

:

At scale for

833

:

Matthew Anderle: Yeah.

834

:

Mm-hmm.

835

:

Randall Stevens: you know, when you see

how big that the actual tur, you know,

836

:

these wind windmill turbines are, but

maybe you can describe what you built.

837

:

We'll, I'll put up the

pictures and video as you

838

:

Matthew Anderle: Yeah, absolutely.

839

:

we, um, we always are trying to push the

envelope, of course, of what we can make

840

:

and, uh, and when we're sticking to a,

a standard, right, the module like 12 by

841

:

14 kind of size, um, there's opportunity

for you to make like a, a double size

842

:

and a triple size version of that.

843

:

Um.

844

:

It's interesting, uh, that it, the one

to one 60 scale, it's small enough where

845

:

you can make some very large components

like a wind turbine uh, and still have

846

:

it in a, in a transportable state.

847

:

Otherwise it'd be feet tall.

848

:

Um.

849

:

It was important for me to

challenge myself and, and, uh,

850

:

get into that kind of micro level.

851

:

Uh, a lot of our rovers that we're

dealing with are kind of in that

852

:

mid-range, like I said, pizza box

or, or, uh, trash can lid size.

853

:

I wanna get very small, so, uh, tiny

geared motors, resin printing to really

854

:

get really finite details out of it.

855

:

And then, and then modeling this

with the, the blades and things

856

:

like that are transportable.

857

:

Um, end up using a bunch of like.

858

:

rare earth magnets and things

to hold things together.

859

:

Well, I, it spins around and, and

kind of scaling things down to the

860

:

right speeds and right size, uh,

was a, a good challenge and, and,

861

:

uh, it tested the capabilities

of these, uh, different printers.

862

:

So I, I took a, a standard

wind turbine that, uh, is.

863

:

About the 2015 era, right?

864

:

They, they've changed over time and they

get larger and bigger and, and, uh, and

865

:

so about the 2015 era, I made the, a

scale model of this that actually spins.

866

:

So, um, as we set it down the tracks

and we start running trains, the

867

:

wind turns right and start to turn.

868

:

And, and you get that effect of, uh,

the size of these next to a locomotive

869

:

and next to a barn and, and what

they would look like in the field.

870

:

And, um, and I would, I would admit

it that I've, I've been questioned

871

:

if that's actually true scale or not.

872

:

And

873

:

Randall Stevens: huge.

874

:

Matthew Anderle: it is exact, it is exact.

875

:

Randall Stevens: how big they are

when you see it next to, you know,

876

:

a train or a little farmhouse or

whatever it was on the, uh, diorama.

877

:

So.

878

:

Matthew Anderle: it's

actually a big draw though.

879

:

And, uh, and something like that as well.

880

:

It's not a train, but the, the fact

that you get a, a model and you get

881

:

that attention to detail and it moves

and it, and has a, a, a representation

882

:

of what we see in real life, uh, that

that is enough of an inspiration to,

883

:

to bring people over to talk about it.

884

:

And then the trains are like

a compliment on top of that.

885

:

Randall Stevens: I, I've

saved this to the end.

886

:

We can, I want to, I want you to talk

about that pin that's on your lapel.

887

:

Tell us what you're involved with

and, uh, this is pretty cool.

888

:

Matthew Anderle: So, uh, I'm sure

you've seen in the news that,

889

:

uh, AECOM has been selected as

the, uh, design build and program

890

:

management partner for the Olympics.

891

:

And, uh, and my team, including

myself, are involved heavily with

892

:

that, uh, project out west, uh, to

develop the LA:

893

:

Company is, is responsible for any

of the design work that's happening.

894

:

Um, the construction that's gonna

happen to, to renovate or modify venue

895

:

venues, to, to meet the kind of the

new standard for Olympic competition.

896

:

And then, um, all the temporary

structures that have to exist to

897

:

be able to, uh, facilitate people

and, and the power distribution and,

898

:

and concessions, things like that.

899

:

Randall Stevens: I heard, uh.

900

:

I guess maybe the head of the Olympic

committee out there described it

901

:

as, it's like having seven Super

Bowls every day for, you know, three

902

:

Matthew Anderle: For

903

:

Randall Stevens: something right.

904

:

Matthew Anderle: exactly.

905

:

Randall Stevens: uh, Matt, maybe

you can just give her, uh, part,

906

:

part of the backdrop of this is

LA uh, is not gonna build any new

907

:

facilities, so there's not gonna be any

908

:

Evan Troxel: I heard that.

909

:

Randall Stevens: new

910

:

Evan Troxel: Yeah.

911

:

Randall Stevens: So, uh, Matt, his

team and the AECOM, uh, team or, or

912

:

task with, you know, how many, how

many different facilities are there?

913

:

Fif 50 some.

914

:

Is that what you told me?

915

:

Matthew Anderle: We're up to about 60.

916

:

Yeah.

917

:

Randall Stevens: 60 different facilities

have to be converted, sometimes

918

:

converted for use, converted back,

during the games, and then at some

919

:

point converted back like within

days to hand back for its normal use.

920

:

So

921

:

Evan Troxel: Hmm

922

:

Randall Stevens: you think about the

scale, maybe you can just talk a little

923

:

bit, Matt, about, about how you are

approaching this and the scale of

924

:

the problem and, and the fact that.

925

:

Uh, you.

926

:

Evan Troxel: time's ticking.

927

:

Matthew Anderle: Right.

928

:

Countdown timer is on.

929

:

I agree.

930

:

Yeah, so it's unique that

it's, it's Los Angeles, right?

931

:

They have everything and um, they

have the capacity for everything.

932

:

they've hosted the Super Bowl, right?

933

:

They've hosted how many major

events over time, and, uh, the

934

:

venues exist already for all this

elite level competition, right?

935

:

You're talking about.

936

:

Football and baseball and basketball

and, and, uh, any of the, the aquatic

937

:

events, any of the, you know, kind of

skate parks or other, um, aspects of,

938

:

of the Olympics, all of those exist

in a, in some capacity already in Los

939

:

Angeles or vicinity of Los Angeles.

940

:

So, yeah, no new venues.

941

:

Um, but there are some

aging infrastructure, right?

942

:

The Coliseum is, uh,

is one of the original.

943

:

Big Olympic stadiums that, uh, exist.

944

:

It has a torch, right?

945

:

So it has the, the components

from the, uh, the 84 Olympics.

946

:

So we're looking at how do we

modify that to, to meet the level of

947

:

competition that are, are new and, and

kind of contemporary athletes are, uh,

948

:

exhibiting within this kind of sport.

949

:

Uh, so tracks are

slightly different, right?

950

:

The fields are slightly different.

951

:

Um, we are repurposing venues

for things that they may not.

952

:

Originally been intended to, uh, if you

saw I think, um, SoFi Stadium, which

953

:

is now Olympic Stadium is gonna be, um.

954

:

A swimming venue.

955

:

And so we're bringing in Olympic

956

:

Evan Troxel: Hmm.

957

:

Matthew Anderle: and uh,

Olympic Paralympic swimming

958

:

Evan Troxel: Where do you buy those?

959

:

Matthew Anderle: are gonna happen.

960

:

There's a

961

:

Evan Troxel: Yeah.

962

:

Matthew Anderle: So, so that kind of

logistics into how we plan, uh, for

963

:

these venues to kind of transform

for a very short period of time.

964

:

And then repurpose back into, uh,

their existing state for, uh, the field

965

:

to play that they're meant to be is,

uh, is one of the challenges, one of

966

:

the many challenges, um, our teams

have embraced this wholeheartedly and

967

:

are, are well on pace to, to deliver.

968

:

And, um, it's something that, um,

is rewarding in understanding the

969

:

complexity and, and rewarding and,

and, and finding this momentum.

970

:

To be able to kind of transform what

LA's gonna look like for a few months

971

:

and then bring it back to the, the

kind of, the, the wholesome city that

972

:

we all love is, is Los Angeles, right?

973

:

The, the southwest of us?

974

:

Evan Troxel: I am curious on the

transportation side, Matt, 'cause

975

:

you said LA is like well positioned,

but I can't imagine they are.

976

:

Transportation wise, so is there, can

you comment on anything on that side?

977

:

Matthew Anderle: Well, they're

already exploring things in

978

:

Los Angeles that help, right?

979

:

They have autonomous taxi, they

have rail, they have air, they

980

:

have, they're, they're on the coast.

981

:

So there's opportunities for a

lot of different ways to, to, um.

982

:

Navigate to and around Los Angeles.

983

:

Um, that's obviously something of, of our

attention in, in the LA 28 committee's.

984

:

Attention is, uh, it's projected to be

the largest Olympics in the world ever.

985

:

And it's, uh,

986

:

Evan Troxel: Like attendance wise.

987

:

Matthew Anderle: by

988

:

Evan Troxel: Hmm.

989

:

Matthew Anderle: to Olympics ever.

990

:

Uh, so that's not going unnoticed

and it's something that, uh, is at

991

:

the forefront of everybody's mind.

992

:

And, um, because there's no new

venues, I think that allows us.

993

:

The opportunity to refocus on some of

those other challenges ahead of us.

994

:

our, our group ACOM is really responsible

for the venues and anything that's

995

:

Evan Troxel: Okay.

996

:

Matthew Anderle: of the site, but we're

working closely with LA 28 and, uh, and

997

:

the city, the state, the county, um,

everybody to kind of help navigate that,

998

:

understand what the venue impact looks

like, understand what the site conditions

999

:

are, and, um, and work together as a

o, to deliver the Olympics in:

:

00:48:16,949 --> 00:48:17,309

Randall Stevens: It's kind

:

00:48:17,321 --> 00:48:17,951

Evan Troxel: How exciting.

:

00:48:18,089 --> 00:48:19,289

Randall Stevens: times technology wise.

:

00:48:19,289 --> 00:48:21,929

'cause obviously, you know,

autonomous vehicles and things

:

00:48:21,929 --> 00:48:24,989

are moving pretty quickly and

starting to come into the market.

:

00:48:24,989 --> 00:48:30,389

So, know, three years from now for sure

you would think that there's gonna be, you

:

00:48:30,521 --> 00:48:30,731

Evan Troxel: Hmm.

:

00:48:31,229 --> 00:48:34,409

Randall Stevens: so it's, it's gonna

make an awkward time to plan for that.

:

00:48:34,649 --> 00:48:35,399

Do we plan for

:

00:48:35,444 --> 00:48:37,479

Matthew Anderle: If, if I

could project what technology

:

00:48:37,479 --> 00:48:38,379

would look like in three years,

:

00:48:39,149 --> 00:48:39,569

Randall Stevens: right.

:

00:48:39,909 --> 00:48:40,629

Matthew Anderle: unstoppable.

:

00:48:40,629 --> 00:48:40,899

Right?

:

00:48:40,899 --> 00:48:43,569

But, uh, that, that's a, in

my crystal ball right now.

:

00:48:44,399 --> 00:48:44,909

Randall Stevens: bet.

:

00:48:45,269 --> 00:48:48,089

Uh, yeah, I mean it's usually

the, it's like, it's kinda

:

00:48:48,089 --> 00:48:49,259

like the world's Fair, right?

:

00:48:49,264 --> 00:48:52,589

It's the, it's a great venue for

showing off new technologies and stuff.

:

00:48:52,589 --> 00:48:52,859

So I

:

00:48:52,974 --> 00:48:53,259

Matthew Anderle: It is.

:

00:48:53,999 --> 00:48:57,389

Randall Stevens: the world coming, uh,

coming to LA in:

:

00:48:57,719 --> 00:49:01,439

we'll all get to see, you know, we'll

have to, have to make some plans,

:

00:49:01,469 --> 00:49:04,019

Evan, to go out and, uh, and, uh, part

:

00:49:04,046 --> 00:49:04,766

Evan Troxel: That would be awesome.

:

00:49:04,769 --> 00:49:05,669

Randall Stevens: the:

:

00:49:05,846 --> 00:49:07,766

Evan Troxel: I just left

LA a couple years ago.

:

00:49:07,766 --> 00:49:08,036

I,

:

00:49:08,099 --> 00:49:08,459

Randall Stevens: moved,

:

00:49:08,606 --> 00:49:09,626

Evan Troxel: be ready to go back by then.

:

00:49:10,256 --> 00:49:10,436

Yeah.

:

00:49:10,704 --> 00:49:13,254

Matthew Anderle: well and compliment

to those challenges ahead of us.

:

00:49:13,284 --> 00:49:13,854

Um.

:

00:49:14,244 --> 00:49:19,104

It, it's also rewarding to know that AECOM

in partnership with LA 28 is bringing,

:

00:49:19,524 --> 00:49:21,774

uh, the first Olympics delivered in bim.

:

00:49:22,014 --> 00:49:22,284

Right?

:

00:49:22,344 --> 00:49:26,334

It's, it's, to me that might be a little

difficult to understand that, that it

:

00:49:26,334 --> 00:49:29,784

hasn't happened yet, but it's, it's gonna

be the first Olympics delivered in bim

:

00:49:30,144 --> 00:49:32,664

and we're gonna be using some of those

advanced tools and the way we construct

:

00:49:32,664 --> 00:49:34,554

and manage our activity on sites.

:

00:49:35,034 --> 00:49:38,604

So, uh, those are all rewarding metrics

to have as part of the success story.

:

00:49:38,604 --> 00:49:41,694

That is, um, ACOM, LE

28 in the, the Olympics.

:

00:49:42,881 --> 00:49:45,521

Evan Troxel: I can imagine Matt,

too, with this like robotics

:

00:49:45,521 --> 00:49:46,541

side that you guys are doing.

:

00:49:46,541 --> 00:49:50,651

You said LA's got a lot of aging

infrastructure, is I, I imagine where,

:

00:49:50,861 --> 00:49:52,181

where these two things go together.

:

00:49:52,211 --> 00:49:52,421

Right.

:

00:49:52,854 --> 00:49:55,059

Matthew Anderle: I, I can

imagine they do also, I can't

:

00:49:55,416 --> 00:49:55,426

Evan Troxel: Okay,

:

00:49:55,449 --> 00:49:56,949

Matthew Anderle: on everything, but, uh,

:

00:49:57,046 --> 00:49:57,336

Evan Troxel: sure.

:

00:49:57,669 --> 00:50:01,299

Matthew Anderle: there's, um, the

toolkit that we have available is

:

00:50:01,334 --> 00:50:04,299

certainly, uh, something that we're

applying to our approach to the games.

:

00:50:04,654 --> 00:50:04,894

Evan Troxel: Cool.

:

00:50:05,852 --> 00:50:09,237

Randall Stevens: Uh, specifically Matt,

tell, tell more about what your role

:

00:50:09,237 --> 00:50:11,997

is and what team you're leading and.

:

00:50:12,427 --> 00:50:12,727

Matthew Anderle: Sure.

:

00:50:12,757 --> 00:50:17,917

So, um, my, my official role as a platform

manager or platform director for ACC, and

:

00:50:17,917 --> 00:50:20,767

that's our common data environment for

everything that we're doing on the games.

:

00:50:21,937 --> 00:50:26,167

my team and, and the extent of my team

is supporting all of those, uh, digital

:

00:50:26,167 --> 00:50:30,787

delivery practices that we're using, uh,

the strategy that we're employing to, um.

:

00:50:30,927 --> 00:50:35,097

Deliver the games, any anybody who's

involved, including our internal teams, to

:

00:50:35,457 --> 00:50:37,197

external stakeholders all over the world.

:

00:50:37,557 --> 00:50:40,647

And it's, uh, it's something that we're

kind of leveraging all the experience

:

00:50:40,647 --> 00:50:43,797

we've had in the, in the history of

our projects across different market

:

00:50:43,797 --> 00:50:47,877

sectors to, uh, come together and

deliver 60 venues at the same time,

:

00:50:48,267 --> 00:50:49,947

um, at the caliber of the Olympics.

:

00:50:50,067 --> 00:50:53,937

Um, one of the challenges that, that

I of project to my team and anybody

:

00:50:53,937 --> 00:50:58,077

who joins our projects is that it's

an, uh, immovable schedule, right?

:

00:50:58,137 --> 00:51:00,027

We have a deadline that has to be met.

:

00:51:00,777 --> 00:51:03,747

It is something that is challenging

in the complexity of all of

:

00:51:03,747 --> 00:51:05,997

these parallel activities that

are happening on the project.

:

00:51:06,687 --> 00:51:09,507

it has to be the sophistication

of Olympic competition.

:

00:51:09,567 --> 00:51:13,077

It has to be to the caliber

of, of worldly best, right?

:

00:51:13,077 --> 00:51:17,907

And if it's not delivered to that scale,

um, then it's, it's not a success story.

:

00:51:18,237 --> 00:51:21,597

And, and like I said, we're well on

track to deliver and, and our teams are

:

00:51:21,597 --> 00:51:23,817

fully engaged with making that happen.

:

00:51:23,907 --> 00:51:24,237

So.

:

00:51:24,814 --> 00:51:25,144

Evan Troxel: Nice.

:

00:51:25,267 --> 00:51:28,057

Matthew Anderle: It's a great project

and it's, uh, it's, I don't wanna say

:

00:51:28,057 --> 00:51:30,217

we're just getting started 'cause we've

been working on this for quite some

:

00:51:30,217 --> 00:51:33,727

time with, uh, with pre-planning and

master planning and, and our teams that

:

00:51:33,727 --> 00:51:37,267

are doing the sports alignment, uh,

with the city and, and all the venues.

:

00:51:38,227 --> 00:51:43,237

But it's, uh, it is, it's years ahead and

it's, uh, a known deadline for all of us.

:

00:51:43,717 --> 00:51:44,017

And,

:

00:51:44,214 --> 00:51:44,424

Evan Troxel: Hmm.

:

00:51:44,647 --> 00:51:46,297

Matthew Anderle: the anticipation

is growing every day.

:

00:51:47,364 --> 00:51:48,504

Evan Troxel: It'll be

here before you know it.

:

00:51:48,522 --> 00:51:48,742

Randall Stevens: Hmm.

:

00:51:49,528 --> 00:51:50,068

That's great.

:

00:51:50,758 --> 00:51:52,858

Well, Matt, thanks for joining.

:

00:51:52,858 --> 00:51:56,908

I'd be remiss if I didn't say

the only thing better than Mr.

:

00:51:56,908 --> 00:52:02,038

Matt Anderly is his wife Katie,

who, uh, who also works at AECOM.

:

00:52:02,098 --> 00:52:04,798

Uh, but they're, they're

just a great, great couple.

:

00:52:04,858 --> 00:52:05,908

Uh, always fun.

:

00:52:06,028 --> 00:52:06,668

My wife and I actually.

:

00:52:07,418 --> 00:52:11,258

When we went up there last month, my

wife, uh, Emily went with me and we got

:

00:52:11,258 --> 00:52:14,618

to have dinner with, uh, Katie and Matt

and hang out and got to see, uh, Santa's

:

00:52:14,708 --> 00:52:19,148

workshop, uh, in person, which for those

of you that wanna stick around, I'm

:

00:52:19,148 --> 00:52:22,628

gonna try to, you know, we, we will have

interspersed some of this, uh, during

:

00:52:22,628 --> 00:52:26,888

the conversation, but I'm gonna put some

extended, uh, video and photos at the

:

00:52:26,888 --> 00:52:30,398

end of this so people can kind of get

a, get a glimpse of what it looks like.

:

00:52:30,458 --> 00:52:33,398

Uh, at, at the little work, not little.

:

00:52:33,488 --> 00:52:36,398

It's a, it's a nice workshop up

there in, uh, Columbus, Ohio.

:

00:52:37,434 --> 00:52:38,394

Matthew Anderle: Full of inspiration.

:

00:52:38,484 --> 00:52:39,129

That's how I go.

:

00:52:39,793 --> 00:52:40,393

Randall Stevens: is a lot of

:

00:52:40,655 --> 00:52:41,045

Evan Troxel: Nice.

:

00:52:41,113 --> 00:52:44,053

Randall Stevens: we'll convene

everybody down in Chattanooga, uh,

:

00:52:44,053 --> 00:52:48,253

next summer so we can see the, uh,

world's largest, uh, train layout.

:

00:52:48,864 --> 00:52:50,214

Matthew Anderle: Absolutely, absolutely.

:

00:52:50,274 --> 00:52:52,254

And, and, and compliments to Katie too.

:

00:52:52,254 --> 00:52:55,674

She's on the Olympics team

with us and, uh, is part of

:

00:52:55,674 --> 00:52:56,724

our platform management team.

:

00:52:56,724 --> 00:53:00,174

So, um, a key personnel in,

in delivering the games.

:

00:53:00,294 --> 00:53:05,154

Um, so both of us are heavily involved

and, uh, and, and love every day of it.

:

00:53:06,100 --> 00:53:06,490

Evan Troxel: Nice.

:

00:53:06,898 --> 00:53:08,098

Randall Stevens: Well,

thanks for joining us, Matt.

:

00:53:08,874 --> 00:53:09,084

Matthew Anderle: Yeah.

:

00:53:09,084 --> 00:53:09,594

Thank you.

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About the Podcast

Confluence
The director's commentary track for AEC industry software development.
The Confluence podcast is the director's commentary track for AEC industry software. Go behind the scenes with us to learn how and why decisions were made in the creation of your favorite software for the architecture, engineering, and construction industries.

It's a collaboration between Randall Stevens of AVAIL and Evan Troxel of TRXL.

About your hosts

Evan Troxel

Profile picture for Evan Troxel
An industry-leading design and technology expert with a passion for connecting people, Evan is a licensed architect in California and is most well known for his podcasts that focus on the AEC industry.

He has over 25 years of experience in the practice and technology in the architectural profession working with large teams to deliver large public projects for clients. He now brings his experiences together on the Archispeak and TRXL podcasts, and now on the Confluence podcast.

Randall Stevens

Profile picture for Randall Stevens
An AEC industry veteran with 25 years of software development, and sales and management experience, Randall offers a unique combination of expertise in software and graphics technology — coupled with a background and degree in architecture.

In 1991 he founded ArchVision, a software firm specializing in 3D graphics, specifically Rich Photorealistic Content (RPC). Through ArchVision, Randall has built an extensive network with the industry’s leading experts, architectural firms, and visualization software companies, which led him to product development of the AVAIL platform.