In this episode, Audrow Nash speaks to Jason Richards, CEO at DaxBot. DaxBot makes a charismatic robot for food delivery. Jason speaks on their delivery robot, their crowdfunding campaign, DaxBot’s revenue model, working with lawmakers to have robots on the sidewalks, and Jason teases their realtime operating system, DaxOS.

Start

Introducing Jason and Daxbot

Choosing not to have Dax talk

Human-in-the-loop and controlling Dax

Deploying Dax

Daxbot company

Crowdfunding

Dax and the novelty effect

Revenue model, robot-as-a-service, and partnerships

Stairs?

Laws around robots on the streets and working with lawmakers

On not doing silly things to make

Timeline for Daxbot

DaxOS

Links

This is a conversation with Jason Richards. Jason is the CEO of Daxbot, which makes a charismatic robot for food delivery. We talk about deck spots delivery robot, their crowdfunding campaign, that spot revenue model, how Jason works with lawmakers to have robots on the sidewalks. And Jason teases their real time operating system. DaxOS. This is the Sense Think Act podcast. And thank you to our founding sponsor, Open Robotics. Now, here's my conversation with Jason Richards. Would you introduce yourself?

Sure, you bet. My name is Jason Richards. And I am the CEO of Daxbot.

Sure, yeah. So Daxbot is a robotics company that started out at a research and development lab back 2015, the founder, started a couple other companies, pretty successful guy, and decided that he wanted to create a research and development lab to, you know, what is the next wave of technology that we can get in front of, you know, and so, in 2015, one of the thoughts was, okay, well, we need robots to be able to do things. And there's plenty of plenty of robots in the, you know, in the workforce, you know, more in factories and things like that. But how do we bridge the gap into the next generation of robotics, where you have robots that are on the streets, similar to, you know, iRobot? Before the robots go bad kind of thing? It's like the movie being able to say, yeah, like,

Not No, no, not that company. No, yeah, the movie, right. So you can tell a robot, Hey, pick up that, and go watch that window. And robots are smart enough to go and do it in human space. So that was the idea. And looking at what things could be most helpful out of the chute, is the delivery seemed like a natural first thing that a robot could do that would be pretty simple, you know, simple tasks that would be helpful to humans. So so that's where the idea came from. And so as of recently, we just got through restructuring companies now we're dexpot, Inc. and now we're able to go after and commercialize and, and have robots now being deployed to different states around the country where you before? Yeah, so before is Nova dynamics. So Nova dynamics was the research and development incubator. And they've got several projects, Dax as the robot was kind of the big one. And so with that platform, we knew that at some point, it has to move out of the r&d Lab and into its own entity that can be commercialized and become something Gotcha. So. So that was the next step. So as of last year, when you know, all the research and development last year, when COVID hit, it was a great opportunity to start getting robots out in the field, in our local hometown, because restaurants, people aren't coming to, you know, restaurants are closing their doors. But people aren't wanting to see people. So it seemed like a great space. And it was, you know, for that beta test, being able to take robots that we have go to the restaurants, pick up food, and then ticket to people's houses, you know, all without seeing a human was really highlighted the need for this type of technology. And it is well received. And it was a great, great beta test for us. So January of this year realizing okay, we've got a product that is ready to go awesome. So commercialized and

here we go. Hell yeah. Tell me can you describe what Dex looks like?

Yeah, so Dax is a robot? It's about right. Yeah, yeah, if you're, if you're watching the video, you can see the one behind and it's about three foot tall, and white and black, kind of a reverse tuxedo type situation. And so you see, you see, Dax has got a fully articulated neck so that he's able to look all around and look up and down also has LED panel eyes. So the eyes are able to be expressive, you know, whether it is being able to be hearts or you know, I love you going to sleep blinking, so that it has some sort of emotional response from another human. So that is and then the, the cargo that's the thing that everybody asks, well, if it's the delivery robot, where's the cargo bay, and it's actually inside the stomach. So what you think of the stomach of this little creature, for people that haven't seen Dax before, I'd encourage you to go, you could check out Dax spot.com. You can see pictures of him and that kind of thing, but, but inside the drawer, which is where his stomach is, is where the payload goes. And then inside that is, you know, heating elements. We've got to design for a refrigerator so that we can do that's cool pharmaceutical delivery. Yeah, things that need it, which is pretty. That was a pretty astounding thing from the engineers perspective to be able to build a refrigerator Inside the robot, obviously, it takes up a lot of space with a compressor and, and heat exchange, especially in that type of area. But fascinating, and we did a lot of cool testing with that one. But so that is is Dax.

And so, to me, Dax, I was gonna say refrigerator, like a little like college dorm freezer kind of thing. Right? It's kind of looks like one of those. And then it has this articulated kind of like hexagonal head that has the LED lights on it. And that head is on a neck that seems to have a few degrees of freedom, which I'm sure we'll talk more about that later. And we can't see it in the video now because of how the cameras positioned. But Dax is on tank treads, right? Yep, gotcha. Correct. And to me, Dax looks a lot like Wally without arms. And like, you say, like, the belly is where you store the payload. So whatever you're delivering, like in Wally Wally was designed to have that trash compactor there and its belly. So it seems kind of similar to me. Right. And the tank treads. Yeah, these kinds of things. Yeah, we,

we joke about the fact that Dax kind of looks like Wally and Eve had a baby. And that baby.

That is right, because of the coloring. Yeah. And the sleek design color in the scheme. Yep. Yeah, yeah, exactly. Okay. Tell me a bit about the neck. Or the head, I guess. Yeah. Yeah.

So the getting the biggest piece that we wanted to solve was, you know, the human robot interaction piece. There other than delivery robots. There's a lot of people that will ask about that, you know, why? Essentially another delivery robot. And it's it's kind of funny because, you know, Dax was built people are familiar with starship, Dax and starship started almost the exact same time not familiar with starship as far as what a starship? Oh, yeah. So start. Yeah, so starship is a delivery robot on some college campuses. And if you look up delivery robots, if you just Google it, you'll find you know, kiwi, bot, and starship. And there's some others. And essentially the same, the design is exactly the same. It's about it looks essentially like a cooler with a couple of wheels on it. And so it has a payload and it's, it's useful in some applications. But with the the neck and the eyes, it was more of, you know, how do you create something that is going to be accepted in human pedestrian spaces. So so that's where the idea of, you know, articulating neck head, not putting sensors all over the place, and the founder, you know, dexpot really wanted to make sure that it wasn't creepy. You know, there's, there's plenty of really cool, like, mechanically amazing feats that people are coming up with, you know, as far as like mechanics of robots, you know, bipeds, those types of things. But if if, for example, you just saw, you know, two legs, two robotic legs running you down the street, you'd think that Armageddon was happening, I mean, that that would be a creepy thing. So wanting to make something that would be accepted in human space. So there's a lot of work that went into that, of how do we make a robot that people want to have around? So So delivery robots, most of them have that design of a cooler on wheels, and about two feet off the ground. And it becomes an annoyance for a lot of people, because it's it's in the way, similarly, people don't really, people don't even want bicycles on sidewalks, right? And it's a human on that bicycle, but it's annoying and pedestrian space. And so they make bicycles

that cars have. And so I don't know if it's quite the same thing. I get that they're also annoying, but perhaps it's like, they go fast. And there's the potential to like, get hit by a bike bicyclist or something like this or them for to come out of nowhere. Yeah. Whereas I don't know that small tub robot would be quite the same thing. Or what do you think?

No. Yeah, the biggest piece had to do with with visibility is not being you know, not being able to see it. If it's it knee height, it's different than if it's it, you know, waist height, or, you know, shoulder catches.

So it's like a mobile piece of furniture to trip over if it's short, and that could irritating. Okay.

Yeah. Yeah. And same way. I mean, you know, people don't like skateboarders on on sidewalk. Yeah. Again, moving fast, though. Remote Control often, yeah, some of it could be moving fast. And it's in a way it's becomes a tripping hazard, that kind of thing. And so the interesting thing with Dax is that with all the testing we've done on the HRIS side of it, is you know, especially kids love Dax, it's about the same height and so they can give it a hug, and it's looking them like almost either with very cute and with and with the neck itself. And the reason that we didn't want to creepy with sensors all over the place, people ask, well, it has 360 degree cameras in it, for example. You know, it's kind of an assumption a lot of engineers have, it's like, No, there's not 360 degree cameras in it. And people always want to know why it's like, well, you don't have 360 degree cameras and you know, you can kind of hear that their stuff behind you. And so you can, you know, you have some sense and awareness of what's around you. But you're not a spider, right? You don't have this spidey sense where you can you know that something's behind you. So in the same way, that's where the articulating that came from, you know, you could have something that that knows everything around it in a 360 degree view, or you have something that actually is more like, you know, more like a dog or a human, where you actually have to turn your neck around to see what is actually going on. But yeah, and so even those those pieces, it gives it a feeling that it is actually alive, instead of just being a machine, which why not? It actually is machine.

So I mean, I'm thinking of this thing, where it's like airplanes don't flap their wings kind of thing. So I mean, we can draw some inspiration from biology. But where do we end Drawing inspiration? From biology? Absolutely. And I wonder, I would think it would be possible to use cleverly hidden sensors and to have the articulating neck, but have the articulating neck not necessarily tied to a vision system. Why Why limit it to having the vision system on the articulating neck instead of just having hidden sensors and this kind of thing?

Yeah, that's a good question. I don't know, the, the founder when he went through all of this, there was a lot of there was a lot of, you know, reasoning and things like that. And again, making it more a phrase that we use around here is anamorphic. You know, it's not anamorphic. It's not an ad. Cannon morphic. I don't know who doesn't like thrupp amorphic are more like a like a dog. Yeah. Yeah. Yeah, it seems more like it's a pet than it is a machine.

So anamorphic. So it's like anthropomorphic animal. So when we assume but with cane, but for things like dogs, or whatever it might be, okay, so it's a creature and has some sort of intent when it moves around the world or whatever it might be. Right.

Yeah, exactly. And so one of the things, for example, is, I believe one of the stories I heard is that if Dax you know, robot goes into a situation and needs to go backwards. You know, we as we as humans, don't walk backwards, right? We don't just like walk backwards into into us, yes, we will turn and say, Oh, here's where we're going to go. And then, you know, if we need to have some field division in front of us, we'll be looking back and forth. So in the same way, wanting to train, train the robot, right train the neural net, so that it's not just doing things automatically. So it actually is showing intent, that oh, here's where I'm going. One of the things that we've heard, we actually, we live close to a university, Oregon State University. And one of in starship, one of those competitors is up there. And I haven't heard, I haven't talked to anybody around that really likes them on campus. And the reason for that is because it has to do with intent. So the device will drive up to a street corner, and then stop. And then all the other traffic, the cars are like, What are you doing? Yeah, what do I do? Yeah, is it gonna cross? Am I gonna cross there's no clarity? No, there's no law about right of way. Yeah, exactly. So there's sensors, no signaling, there's, there's no idea, you know, are you going to go am I going to go and so it's, you know, some of these devices have been hit one guy hit by a train that's been hit by a truck, one's one into a train. And so it's, you know, and it has has plenty of sensors onboard. You know, that's, you know, with that one specifically, it's, that's not the problem. But because people don't know what it's gonna do, they don't have any, any idea versus Dax will get to the street corner, and like a human, it will look at you, and it will watch you and follow your vehicle as it drives past. So you know, oh, this thing sits somewhere. And it's aware of what's going on. And it cannot its head, like, yes, you can go Go ahead, or, you know, shake its head so that people know, Oh, you want me to go? Versus you're gonna go right. And so there was a lot of there was a lot of thought and intentionality into the neck. Yeah, isn't just necessary for the neck sake, but it's more for communication, it looks one of the design,

it looks to me. So thinking of like the founders perspective, and this kind of thing, perhaps it had something to do with making it so that so I mean, if you have sensors everywhere, and you can get a really good rendering of the world and this kind of thing. You can design behavior that uses that understanding of the world. But in this case, you're kind of constraining the behavior of the robot to be something that seems more natural. In like, it has to go and look behind it. There's something if it's going to go and back up or if it wants to, like look both ways for the street, you have to do that with the head. And it almost so it basically constrains the developers to like, I don't know program more lifelike behavior in it so that it operates in the world. I could see that being a clever way of doing that kind of thing.

And for for engineers, specifically, mechanical engineers, they would much prefer to have the device to be a cooler, right? Just right. Yeah, that's it, that's a much simpler thing than a fully articulating neck was dual pitch motors. Right?

Yeah. Or just a sensor information would be probably more valuable. Absolutely. The who cares if it looks like a cooler, but I get your meaning that for like, sensors everywhere and full 3d map of the whole environment that it's in and this kind of thing?

Yeah. Yeah, absolutely. And we, you know, obviously, we got, you know, that technology to be able to do that, so that Dax is able to learn in 3d space, and you know, instead but, again, more similar to, you know, a human if I'm walking down the street, and I've been down that street before, I have an idea of what to expect, right? I know, there's a curb there. I know. There's a telephone pole. I see. Oh, there's a box there. I've never seen that box before. Okay. New information might not be there tomorrow. Right? So it's not something that that really comes in. But because everything is changing in such a rapid space, again, on a factory floor,

you mean in the environment? Like walking around?

Right, yeah. And environment or walking? Right. If you're walking downtown, you know, in a metropolitan area has a lot of moving parts. It's changing all the time. Yeah, exactly. So so being able to have something that is more lifelike to be able to adapt in that environment. And it seems more natural in that environment. Actually, pretty interesting.

So what sensors are on this robot on the Dax robot?

Yeah, so despair division is is one of the two it has

a stereo that has two cameras beneath the kind of chin. Yes, something right below the display. Right. And

yeah, so yeah, where you see the display of the eyes is where that

just been, you know, just beneath it. Yeah. Cuz I think I see that a little circles from the cameras that it has. So you have the two cameras. And from that, you can infer some 3d information about what's in front of the robot. Okay. Yeah. Anything else? I mean, I imagine there's encoders and things on the wheels, or the track. Oh, yeah. What, uh, and then all the motors have sensors and things. But what else for perception?

Is it just those cameras? Maybe microphones? Yeah. Yeah. So it's got, yeah, it's got stereo microphones. See, so you can hear what's going on. Again, kind of that sense. If you're, if you're a human, you can hear somebody coming up behind you, right? You don't have eyes in the back of your head, but you can hear that something is happening. And you're more aware of your environment that way. So, so yeah, those those. It's fun. When I when I talk to people about sensors, a lot of times they're thinking very unilaterally, and they're thinking about, like Lidar and

Yeah, exactly. Yeah. Like LiDAR, ultrasonic. I

mean, I'm honestly surprised. You don't have like a plane or lighter or anything in there. But if you can do everything with vision, that's great.

Yeah, yeah, it's, it's pretty fascinating, obviously, yeah, the tracks have sensors, things like that, you know, when we're going into, you know, autonomy, things like that. Being able to have tracks to be able to know, even if you lose, you know, GPS signal and that kind of thing, you're able to know, within, you know, centimeter to where you're at in your thing.

The tracks are very accurate for encoding it. And that's probably because they don't slip as much as wheels might.

So Gotcha. Okay, so going back to the neck, you have these two cameras, and those are that's the majority of the bed that is the big perception sensor, the two cameras, and then you have stereo microphones, or whatever it's called, so that you can tell directionality of the sound, right? Yeah. Great. That's that's pretty much it for perception. Other than like, actually, I forget what it's called now, like dead reckoning your position for from the tracks and this kind of thing.

that's it you've like, are there like capacitive sensors? So it can tell if it's being pat or hugged or anything like this? Or how do you detect like, a person is your buyer interact? I guess the cameras would do that. But do anything for a person touching it or anything?

No, no, not. We've, you know, talked about that a little bit. It's not, we don't know, how helpful that would be at this point. You know, everything, everything has to have, you know, some lead time and stuff like

you know, just which I like to do is that just takes time. Gotcha. Yeah, yeah. Just development time. You know, and so what you know, weighing priorities, which is the most important thing totally, but yeah, with with you know, the vision for example, you know, if if somebody sneaks up behind me and touches me, yeah, I would know that and maybe the robot doesn't at this point might being able to hear this. Yeah, exactly. Somebody is coming up behind me. I can look back and be like, Oh, hey, what's going on? And then you know, we can have a conversation so no, no perceptions. As far as that's gotcha

is just curious with like interacting with little kids and stuff with like the little kid with patted on the head and would know with being pat on the head. Oh, yeah. But

people people are hugging it all the time.

Yeah. Okay, so the neck. Tell me about the neck. So it how many degrees of freedom does it have? What kind of things gonna do? Yeah.

So not wanting again, not wanting to be super creepy. So we've limited the range.

So we can't go around like, a hole or something.

Yeah, we don't want this. It's Halloween. Yeah. Yeah, robot, right. Yeah, exactly. So it's a limited a limited range view, just just like a human would be. So it doesn't it will go back, probably a little farther than a human would by itself. Turn my neck, I can get about 90 degrees. But it doesn't go much further than that. So we have we also do a full 180 either. And so it's about it's about 150 degrees. So that's pretty harsh. And, you know, basically looking over your shoulder, right, you can look back and see what's going on. Yeah. And then And then, you know, down basically similar to a human right, you can sit down touch your head. And then the other problem is, you know, looking, looking up, you've got the back of the the head,

right, the Yeah, because the cameras are just underneath the chin, in a sense. So it really does like to look up. Yeah, to clear the chin. Right. Yep. Yeah, exactly. So,

yeah. So that's it fully, fully articulating in all of the directions.

That's two degrees of freedom. Can it turn sideways? I think it probably can. Right?

Yeah. Yeah. Being able to kind of, yeah, tilt the head, like, one of our Yeah, and that's one of the one of the most favorite ones that we have, you know, especially when we're interacting with kids, or they want to play with the robot. And so the robot kinda like a dog, like, you know, caulk its head and look at you funny. So that's one of the one of the things that we love doing with people. Yeah. Like, and then, and then a couple sounds that we put into the robot. So for them, they sound in some of the videos, which is interesting. I mean, Pixar did a wonderful job. So

Yeah, absolutely. Yeah. But it's, it's pretty fun. One of the in its, you know, with the sounds, people ask, you know, if it can talk in, in some language, you know, English or whatever? And the answer is, well, yeah, tech, technologically, that's pretty simple to do. Yeah, but we've made a decision to not and again, the reason for that is when you don't expect a dog to talk back to you, you know, in in a language, but it will bark and you can you can understand with with nonverbal communication, what is going on. And so in the same way, as we, you know, work with different robots in urban spaces, and they would talk to you in English, it doesn't matter how nice the robot is trying to say something in English. It comes across route, you know, you don't expect a device to be telling you to get out of the way, right. It's like, well, that's, that's kind of, versus a robot that is just making sounds, you know, more RTD to ask, then, than anything else, right? So that you, you understand, like, Oh, this is asking me to move. I was actually just having lunch today. It's at our local Mexican restaurant, and we have a robot down there that's doing deliveries all the time. And the robot had had come inside. And then there was a cup in the way where it's supposed to park. And so it's looking down there looking up looking around, you know, its head like, hey, come over here and putting sounds and then just somebody that was at the restaurant looked at it was like, oh, it's trying to tell me something went over, take the cup, got it out of the way. And then the robot was able to say thank you turn around and back into its spot. So one of your robots you're saying? Yeah, yeah, one of one of the ones like this. Yeah. So So with Yeah, so it a nonverbal communication, and that human robot interaction pieces, again, a lot of stuff that we've we've studied. So it's where we put a lot of time and effort into

Yeah, it seems like a thing of setting expectations. Because I think if something talks, we expect that it can really talk. Right? And then it's frustrating when it immediately doesn't recognize you, like you could say any arbitrary complex thing, and it would have no idea unless there's someone behind the scenes like this.

Right? Yeah, like a web chat. Yeah. You know, mean, typing, and you're like, No, this is definitely this isn't a human

talking. Yeah, the robot would be similar to that. Otherwise, yeah, I've seen that quite a bit from like different human robot interaction research where they want to set the expectation low. So that they can not over promise.

Right. And obviously, you know, other companies have done a good job of overcoming that barrier by having an actual human you know, via like a computer screen on the other side. And then you're talking face to face with a human right? The robot just happens to be, you know, the carrier. It's the media of the iPad, for sure. Yeah, exactly.

So do you. So how much of the robots control? Is a human in the loop? Like tele operating the robot? And how much is autonomous? At this point?

Yeah, at this point, the, the autonomous piece is almost strictly for navigation. So now that part's out of the way, one of the things obviously, the the software guys, they're really excited about the HDRI components automatically know facial recognition, somebody happy, sad, how do I some emotion or act? Yeah, yeah, putting them putting emotion. But you know, while it's on the job, if you will, you know, especially with disparity vision, and making sure that, you know, collision detection and avoidance and things like that is all working, it's going down a path to making sure it's not going to run into something, but at the same time, it comes into an obstacle, you know, it hits an obstacle, not hits an obstacle, it sees an obstacle stops, and then can look around. And it's kind of like, you know, looks like it's looking at flowers or trees are cars that are passing by. So that, so that is more natural than, you know, a robot that just drives you know, gets to a point and then just kind of sits there for Yeah, so. So all of the the human interaction pieces have been with tele operating, you know, having somebody on the other end, being able to emote, and it's been really fun to, again, experiment in a pretty tight loop. So you can see what do people react to? And what do they want? Like, what do they want to see from this robot on a emotional or interaction basis? And then once they have that, you know, now that we've had that we have some really good data now, just programming right? This program, like, okay, when this than this, yeah. And then the robot can know what to do in certain situations.

So when so the robot will autonomously go from point A to point B. It does it uses GPS or how to do that.

Yeah, GPS and, and Dead Reckoning and dead reckoning. So, right? Yeah. So within the tracks itself, it, it knows where it is less slippage, like you'd say, you know, better better than

does it use. Is it doing? It's not generating? I think, in us talking a little bit before the actual recording started. It doesn't do mapping, right, you have to go map an area before the robot goes into that area. Is it correct?

Yeah, for the autonomous piece. Yeah. So when we go into a new area, yeah, we go into a new area, we have, you know, an operator that's doing that piece, you know, going through finding out where the the obstacles are stuff like that. And so here's the road crossings. Here's the dangerous battle. Yeah, don't go here. You know, kind of like kinda like the Waze app, you know. So once we have all that, all that set, then we can say, Yeah, this is a this is a free and clear sidewalk, you can go, you know, full speed. This is a danger zone slowdown. This is a road crossing. We don't, we aren't, you know, there's a lot more programming, we aren't letting the robot cross streets fine. So yeah,

that seems that seems terrifying. For your robot. Yeah. Yes. Yeah. So what is it when someone is going to create one of these maps for the robot? What does it involve? Do they just like a handheld stereo camera to do it like? Or do you just bring a lidar through it? And it just maps everything? Or what like, how do you how do you create this initial map?

Question, we actually, we actually just do it with a robot to drive the robot relocating. Mm hmm. Which does

generate a big 3d mouse that way, and then you annotate it.

Know where it's a little more complex than that. I won't, I won't try to butcher it. Because I'm not one of the engineers on the project. But yeah, but being able to go through. And then with that, being able to process all the data that we need, so we can see, here's, here's what's going on. And it also does a lot of good stuff. When we're doing bigger deployments. One of the things that people really want from our customer base is Dax is really cool. It's a really cool thing, right? It just happens to be cute, and it delivers food. So you know, what it does is kind of an accessory. So when we go to a new area, it brings a lot of goodwill to the, you know, to the people that are getting in as well. You know, we're driving a robot on every path that we can think of, you know, for delivery area, and people are stopping us all the time asking questions, this robots like oh, we're partnering with this person and and so and then also gives us some good information as well for the other connectivity, you know, LTE and stuff like that. So when operators have to jump in, we got to make sure that we have what carrier do we need to use for the different agencies? What bands right Yeah, cuz everywhere. Everyone's A bit different. And so obviously, what will work in here in Oregon is not necessarily the best carrier down in Coronado, California, which is may not be the best carrier in Atlanta, Georgia.

Yeah. Gotcha. Okay, yeah. So you have a map of the environment that you get from driving the robot through it. And then you have the robot navigate autonomously, from point A to point B using kind of like, somewhat labeled map in some way where someone says, this is a crosswalk, this is a sidewalk, these kinds of things, then you get to your destination, and the robot is taken over by someone who's controlling it with a teleoperation setup to actually do the delivery to it. Correct?

Correct. Yeah. So that at this point, knowing that, you know, that's the interaction. It's not just the delivery service, right. It's, it's the experience of having a robot that is being nice to you. Yeah, so that's exactly that's where a human takes over and is able to be interactive. Yeah.

And so for that part, what does it look like, for from the humans perspective? Are they sitting on some sort of, like, video call kind of thing that sees what the robot sees? And they have a bunch of buttons in front of them? Where they can say nod head like this, make this noise? Like this kind of thing for picking the behaviors? Or how does it work?

Yeah, a little more simple than that. A couple joysticks, you know, that have, you know, a lot of lot of pre programs into the joysticks, you know, kind of your over your overview map, you can kind of see where the robots were at, you know, you can monitor several robots at a time. You know, making sure they're staying on path. And then if one needs help, you know, the operator is able to go look into it and see what they need to do navigate around or end of destination, right. Being able to, to contact the person. Let them know that they're their personal copy that's funny for the delivery, like Uber Eats or DoorDash or something. Yeah, when you have to call them and be like, where

are you at? Yeah. Yep. That's funny. So, okay. Let's see. So then, so they're using a simple interface to control the robot while they're doing that interaction. You were saying that eventually, maybe you could automate this kind of thing? Or you or at least part of the interaction now that you're generating data? How and then do you have the customer like rate how enjoyable it was? Or different metrics of it. So you can see how the interaction was and what parts of it they liked and disliked and whatever?

Yeah, good question. So we, so there's not like a Dax app? For example, people aren't ordering food through

Yeah. Well, it's, it's, it's an interesting paradigm. We work with the restaurant and so we'd rather do integration with people so that it's their brand. We just happen to be the Korea robot that's delivered. Yep. Yeah, kinda like, you know, I lived in Seattle and Boeing, obviously the a great company. But, you know, a Boeing airplane could have Alaska Airlines on the side, or it could have delta or United or whomever, right. So. So when I go to get on my plane, I'm not saying hey, I'm on a but am I on a Boeing? I'm no, I'm, I'm with delta this time, or Alaska or whomever? Right? So yeah, it's kind of the same, you know, kind of feel. But, but with that, yeah, so especially here in our local town, it's a small town. And so being able to, you know, we've got their phone number, and then we can ask, you know, direct conversations, and see what people like and don't like we we did a test at a retirement community as well. I mean, the assumptions that we had were kids, we know kids like robots, which I think back to when I was a little kid, and I've got a I've got a eight year old and a two year old, and to them growing up. Oh, yeah. Robots around the street. Like it's just kind of a normal thing, right? Yeah. But so I'd imagine kids probably are good with it. And they do they love Dax, people, our age are, are a lot more amenable to Dax as well, because it's cool technology. So we didn't know how it was going to be received with people in their 90s and, shockingly, Dax were all for overseas. Yeah. Oh, yeah. Again, because it's not it's not a machine to them. It's it's an entity. Right? So when you watch Star Wars, for example, are 2d to into machine. He is but you don't perceive him? Yeah, you see, you perceive him as an as an entity, you know, somebody that you are having conversation with, not just, you know, directing to do a thing so so in the same way when people see Dax, you know, and it's funny, I do the same thing. I know what's behind you know, I know you know, all the inner workings of the robot, but I'll see him on the street while I'm, you know, going to get a taco. And I'm like, Hey, Dad, I'll say hi. And it's so funny. And obviously I know you know, it, doesn't it You know, I'm saying but it's, it's definitely an experience until somebody experiences or sees the difference between, you know, just you know, a cart that can deliver something to you versus having an interaction with a beam. That is a machine. It's starkly different.

Now. So you guys are deploying in your, in your town. So you're in Portland, right? I haven't been to No,

not poor. Oh, where are you? Yeah, not Portland. We're. So Oregon State University Corvallis, which is about an hour and a half south. And we actually are in a small suburb of that in a little town called fellowmen. But yeah, so not Portland. Not Not a huge Metro.

But yeah, small town. How many people to the town? Oh, about 5000. Wow. So

small. It's crazy. Small town. Yeah. Small town. I moved down here from Seattle. It's a big change. It was it was good. Yeah. Yeah. I grew up in it. I grew up in Montana personally. So it wasn't changed to go back. Yeah. Back to a small town. Right. Yeah, we've got robots now that are in Coronado, doing food delivery. Down there. That's been fun. We got some robots that are shipping out to Georgia. Cool. We next week Expo Hell yeah. So we're getting packaged up and shipped to Georgia. And then different deployments. I think Long Beach. We've got some robots in Long Beach right now. Yeah. Deliver stuff. And then. Yeah, and more people are contacting us all the time. Oh, yeah. Yeah,

how many? How many robots are deployed? Right now? Would you estimate?

What really, I could probably do the math in my head. It's not a lot. So we've got the deployment in Coronado, Long Beach,

we definitely use it on the order. Georgia, or is it on the order of like,

yeah, that's about it's about, we've got, you know, got more robots in that that are coming off the production line, but we've got actually in the field working. We've got about

about 10 Yeah, 910. Gotcha. They're doing stuff. Okay. Interesting. How large are you guys as a company? Like how many people are involved?

Yeah, so we've got there's a 18 of us, Hey, we've got the manufacturing. So we got the manufacturing side. That is, you know, getting robots, you know, off the line, then obviously, the operation side and servicing, you know, like, getting data on that, you know, how long do you have to run a robot before the tread needs to get replaced? Yeah. How many miles on their tires, you

know, imagine where you were out fairly fast, too, which is interesting,

surprisingly, not really, actually have lasted a long time, we finally we finally got one that we're like, Hey, this looks like it's certain to how many were out. We should swap this out. I don't actually this actually just happened. I think it was either earlier this week or late last week. And so I asked her Operations Manager, like figure out how many hours we put on this. Yeah, we can put that in our service manual. But yeah. And then obviously, they the engineering team, you know, mechanical and electrical and software and firmware, and yeah, so Yeah.

Gotcha. Cool. And how are you guys funded? For this kind of thing? Have you been accepting investment? Or like, what kind of where are you at in terms of funding?

It's good question. So um, so in 2002, brothers, I'll tell you the story of the founder. So two brothers, they started an internet an ISP. dead broke. I mean, they, they were volunteer firefighters lived at the fire station and paid themselves $50 A week, a month kind of thing, you know, crazy. barely getting by got it got it up and running. And then in 2011, or so kind of limping along there. Since they were firefighters. One of the brothers had this idea because they went to a fire call, they got to the fire station. And the fire trucks were coming back from the call, by the time they got there. He's like, this is stupid. Like, we have the iPhone. I'm gonna build, I'm gonna build an app. And so he built this app called active 911. And last I heard it's about 40% of firefighters in North America use this app called active. Wow. So it's done very, very well. And by his that Joseph and Joseph goal was always to have this r&d lab that I talked about. So in 2015, they started Novo dynamics. And then Dax was kind of the first big project that they said, Okay, five years from now, I think robots doing delivery is going to be a thing. So let's start working towards that end, and more importantly, working towards the future that people want to see, you know, when, you know, again, when people are thinking the future of electric cars, electric cars have been around, you know, since the 80s. Yeah, you know, long people have tried to do electric cars. But it wasn't until Tesla before now, it's something that people want, right? People are like, Oh, that's the vision of the future that we want to see not these weird box things that are glorified golf carts. Yeah, right. So in the same way, you know, with the robot is solving that, you know, what kind of thing do we want in pedestrian spaces? That isn't going to be creepy, that people are going to want to attack themselves to they can do helpful things for people. So that was that was the idea. So the r&d portion is all been self funded, you know, because these other two companies that have done well, it's been self funded up until about a month ago. And so about a month ago, I was actually, you know, January when we said, we need to, we need to commercialize this thing, what do we need to do we need to get investment. Because, you know, building you know, 20 robots is one thing, building a fleet of them. Hundreds is a totally different ballgame. So. So it's actually just about a month ago that we opened up a crowd, crowdfunding campaign through start engine, which is the intermediary, so so it's kicked off. And this first time I've, you know, I've been involved in lots of companies started a couple myself, but I've never gone after investors. So it's a whole new experience for me. You mean crowdfunding specifically? Or? Or even venture capital? You know, filing with the SEC? Yeah. Never. I've always been bootstrapped. Yep. Right. We've always bootstrapped company. So this is the first time going after investors. And it's really interesting, because the the majority of people that don't know us, you know, they don't know who we are. And they don't understand that, that the two brothers like, people that know the two brothers, a lot of people that know them have invested quite a bit because they paid another venture. Yeah. Yeah. And yeah, and they, they seen the robot, obviously, our hometown, couldn't ask for a better reception, you know, from the investing standpoint, because they're like, No, this is our robot. This is our hometown, and, you know, friendly neighborhood robot that we're investing in. But people that don't know us, that have invested. You know, we're saying over $1,000, you know, $1,000 or more, yeah, I've been reaching out to those people. And predominantly, they're engineers, you know, it's people that, that see what we're doing. And they say, Oh, this is cool. Like, this is a cool version or vision of the future that you guys have. And we want to be a part of that. So yeah, so that's where learning, you know, how do we how do we get that message out to more people? So not just engineers, but everyone that's it seems to be? It seems to be interesting that that's the community that is really liking what we're doing.

So yeah, well, they're interested. I don't know, as an engineer, I'm interested in robots. And I imagine it's true for a lot of other engineers.

It's true anyway. And it's not just you know, robotics into you know, every discipline you can imagine civil engineers are like, wow, this is. So it's kind of cool.

So, how was the crowdfunding? What are your thoughts on crowdfunding after? So is it still alive? Or yeah, it's still alive. So at the time of this interview, it is how long will it stay live until? Because it may be I said, it'll be like three weeks before this is published. So

yeah, so the the, the raise is going through either you hit the the first goal that, you know, we can hit with what we filed with the SEC. So we're looking for a million dollars by the end of the year is kind of the the goal and the target that we have, we're about a third of the way there, you know, after been going for about a month, so it will either will either hit that that mark, and the fund will shut off, or I believe it goes until I think it's a six month campaign. So it would go until until April of next year.

Oh, hell yeah. Okay, good. So this episode will air while it is still going if it goes to the six month time. Awesome. Yeah. What have you thought of crowdfunding? It's an interesting model. Does each person get some equity? Or they're just supporting you? Or they like get a tax robot? Or how does it work?

Yeah, so there, yeah, there are different ways of crowdfunding? Yes. You know, we're a nonprofit or something, it's not equity, what we're doing is actually is actually equity. So you're actually getting stuck in the company, which is, is kind of cool. So I've heard horror stories of that,

where you have funding crowdfunding, where you give them equity, because like, you'll have to go and get permission from everyone for all the decisions and eventually, just like veure bureaucracy weighs down the company no longer gets anywhere. That I guess you have clear about their terms kind of thing, if you guess.

Yeah, and everybody so yeah, start engine is the platform that we're using. And part of it is that yes, you do get common, you know, common stock, you know, which is you have shares in the company. But you also are essentially signing over your vote to the CEO, which is me. So, so when anybody says yes, you know, I'm going to put $1,000 into Dax and get, you know, however many shares they're also saying that that, okay, I know that you run minority shareholder, yep. Right. So I am your representative. So I am the vote for the shareholder. So obviously, if people want to talk to me, obviously and let their voice be heard, you know, kind of like a representative government, you know, cool and Okay, I like that a good way better talk to me. Yeah. And then same thing where it's exactly cuz otherwise, you know, your shareholders meetings. Everybody's there by proxy, and I'm the proxy and I'm the boat so, so it doesn't really bog us down administrate If that makes sense, yes, the cap table is, is big. And usually people that don't understand technology very well and the liberalization,

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