welcome to commercial drones FM the podcast that explores the commercial drone industry the people who power it and the concepts that drive it I'm your host Ian Smith hey everybody and welcome to commercial drones FM I'm sitting here in San Francisco with Harris Wang who is the the strategic markets director at velodyne lidar inc and welcome to the show Harris thank you so much for joining us morning here thinking for having my pleasure and maybe you can start off telling us first of all the company about the company about velodyne what is valid i'm sure i think many of you are aware of the name by now it's the name is getting across especially for the autonomous car development we provide a key lidar sensor component that assists in the development and research of autonomous vehicles and recently we receive a minority investment for the Baidu so now we're getting a lot of visibility and I think lady we're seeing a growing interest to use our lidar technology for drones as well nice so autonomous vehicles not just drones so the autonomous cars and things like that correct okay and so what how did you get into a lidar company I mean like what brought you here to velodyne sure so personally my background is worked out to multinational companies fortunately during the industrial space I think now if you look at the next 10 years the biggest revolution will be in mobility both in the air and on the ground so I'm very fortunate be able to join this revolution back to the Bay Area and look forward to what's going to happen in the next five to ten years nice so okay we now we know about a little bit more about the company and how you got there but what is lidar like first of all maybe what does it stand for it spelled li da are so what does lie our stand for and what is it sure is short lidar stands for light detection and ranging now I think most people think of light are similar to lasers how we're shooting lasers and measuring the reflection of the laser see how much time it takes for the photons to come back to the sensor that they call it time of flight so by measuring the time it takes for the light to come back we can figure out the distance and also the reflectivity of the surface this way you can not only not only you can see the measure the distance get a feel for the environment but also you can see the retroreflectors lane markings signs etc hmm interesting so what does that mean exactly so the workflow is you have a lot like how big is a lidar like unit yeah i think if you again search valid I you will see our first model which is fairly large on a lot of the research rd autonomous vehicles now the same technology is getting smaller and smaller now it's light enough to be used on drawings our plans to continue to make it even smaller in the multiples of centimeters and even compaq and cheaper as well in the next you know one to two years and you guys have the like I think people kind of refer to it as like the puck lidar like it almost looks like a hockey puck in similar size but a little bit taller than a hockey puck is that right yes I will say that's our most popular model at the moment and there's it's about 50 times 70 millimeters cylindrical shape and the newest Park light is less than 600 grams Wow how many is that what is that Mike no ounces conversion I have no idea how to convert that to ounces yeah but it's lining up when used on the m100 okay so yeah IM 100 so the m600 for sure that could carry it super easily wow that's that's really cool and so what's the difference then so okay lidar it's essentially could you is it kind of like echolocation or radar kind of but just with lasers yeah I think another way to look at it is if you compare radar lidar and vision or camera radar is like if your work glasses you take it off you have this blur V version up the world you see there's something in front of you but you can make it out what is it because you're not getting enough resolution right where camera you get perfect resolution right you see everything but the death might not be as great hmm and also in in perfect light conditions you might not be able to see the object clearly i think lidar in a way can be used in all light conditions so even in pitch black sure nice and yeah okay and then what about fog is this fog or rain affected or how does that work yeah I think in in those weather conditions affects all sensing technology but because light are the one we have has multiple lasers and you have much more data per second which means the probability of all the lasers being blinded by rain drop by fog will be lower so of course you will lose some of the distance and clarity but there's also a high probably you will see through the rain because light is moving so fast it's like the rain is stopped like the matrix like the movie right yeah about that's awesome and so inside the puck what's happening like there's like a there's like a mechanical well maybe you can describe it like there's something spinning around and how does it how's that working like what's happening inside the little tiny lidar unit sure so we call our technology a hybrid solid-state so we have circuitry mounted inside the park and it has the lasers Andres receivers so we can shoot the light and detect the light coming back at the same time it's rotating anywhere from five to ten these times per second so then you get a nice 360 degree field of view for the environment every second well okay and so that's it's just like spinning around in a circle really really fast and it's just shooting those lasers all around right on average you could get 300,000 points per second so a lot of information about the environment Wow yeah I've seen it so if you if you're listening and you haven't really seen lidar in action there's some really cool I guess whenever you guys do an exhibit somewhere at conferences or whatever and you do a demo you just basically have a lidar unit just set up kind of like on a tripod or something and you can just walk around in front of it and see on a screen in real time like your self kind of walking around and you're just like a bunch of like very accurate dots so speaking of those dots all those points what what you call them how accurate is that is lidar like extremely accurate yeah so the accuracy is depending on which model is 2 to 3 centimeters regardless the distance so we work up to 100 meters and later we'll have a model up to 200 meters so anywhere between that range you will have two to three centimeter accuracy on the results so that means that if I'm standing 75 meters away from the lidar puck itself based on the output data you could actually pinpoint where I am within plus or minus 2 to 3 centimeters for the light our output yes yeah ok that's really cool and so you know we see with the drone industry most people are using most businesses are using photogrammetry and just regular you know video and still imagery how do you compare trast the use of lidar between photogrammetry because with photogrammetry you can also get a point cloud are we talking you know the same type of point cloud here or you know what's what's really the difference here how are you going to are you going to differentiate lidar versus photogrammetry sure I think the at the end of the day the customer want to see a 3d model of the environment of their point of interest and they want to perform measurements for inspection and whatnot but how to get there it depends on the technology used right so we have photogrammetry today we have lidar and as we learn more about the growing usage of lidar in the different markets we hear customers really telling us when to use what technology and I think based on our current understanding light is one of the limitations in photogrammetry are you limited to perhaps some plus minus 1 to 2 hours around noon to get that perfect shot so you have minimum shadow where lidar can work in both dawn and dusk and potentially a night if regulation allows but on the other hand lidar is relatively more expensive at the moment but with a smooth technology adoption increases and we'll also hope to help reduce the cost of lidar in the near term as well but on the other hand photogrammetry from a data standpoint it's a lot to process we hear the word process intensive model time where light are you getting a direct 3d model already so in a way saves all the processing time as well and also in cases where the texture has sharp edges photogrammetry tend to lose some of the resolution mm-hmm where light are still can't give you that physical measurement regardless of the shape you're measuring so the the final result you cut you call like a point cloud usually from lidar data or what's what do you refer to as the result of light are like what's the data type yeah so the output of lidar is a point cloud but those essentially is a collection of relative distances from lidar to the world many people need to convert that into absolute distances so they go through this process called geo referencing by combining the GPS and the IMU data mmm does the does the lidar have a GPS in it usually or is that kind of separate it's a separate component so in the drone world are many of our customers / integrators they will buy the lidar by the GPS and the IMU which tend to be way more expensive than the drill and the light are combined to generate a system used for surveying and mapping and they could achieve depending on the GPS they're using and I a meal they're using they could achieve anywhere from 5 centimeters to 20 30 centimeters of absolute position accuracy mmm okay I see so this is kind of an example that comes up sometimes so if you're just using a drone with photogrammetry and let's just say you're trying to create a point cloud or like a 3d model of a stockpile on a mine site or something like that we usually you know would advise okay if the objective you know it's all about what do you want to do with this data as you said so if the objective is just to create a accurate you know volumetric calculation of the volume of that stockpile then the you know absolute accuracy you know where this stockpile is located on the planet typically doesn't matter as much as actually you know the the relative you know how big is the stockpile like are we accurately recreating this with photogrammetry so with lidar you're saying it's much easier probably a lot more accurate and quicker to get that final point cloud then versus you know traditional photogrammetry and stuff like that yeah so based on what our customers are telling us they've done comparisons for example first scenario is a traditional method using technicians holding a gnss atena walking around the stockpile to getting points before them and general ed vol volume measurements second method is photogrammetry third method is lidar using drawings if they've done comparisons and from a error standpoint you have way more points using lidar versus the manual method and in cases like in perfect lighting you will have better more accurate volume measurements as well so I so the message I think we like to send is really depends on what the application and we advise our customers to choose the right technology for the right problem what our business is using lidar on drones like what kind of use cases have you come across where people are like oh we have to have lidar for this or oh that was extremely extremely useful to have the lidar as opposed to something else what are you guys hearing from customers sure so looking at the market we start to see applications in many industries from argue culture forestry utilities wind turbine inspection etc but I think in summary we see three application use cases number one is surveying a mapping we're calling this passive mode we are there simply correct collecting data using lidar as a payload together with IMU or GPS the second use case is active mode where they're processing the point cloud now in real time which is difficult to do with photogrammetry due to the complexity in the size of the data so this use case is primarily for love of inspections in the market such as wind turbine inspection we have a customer that did that in real time in Germany few months ago and we see more of this SSD major growth area in the next two years and the third is autonomous flight which can be used for delivery huh yeah so just like you're putting it on an autonomous car autonomous like land vehicle same thing with with an aerial vehicle and with 200 meters of range that becomes quite nice I mean you can detect something then that's up to two centimeters in in width I guess so you did mention forestry and that's one of the things so you know photogrammetry is not like obviously not the be-all end-all like only solution like you have to use what works for the objective you want to accomplish so one thing with photogrammetry is it's very hard to penetrate tree canopy and so with lidar then the way that I understand it and correct me if I'm wrong then you're shooting all those laser beams basically out and any area there is to penetrate through the leaves in a tree you're kind of getting all the way down to the to the floor of the I guess forest or something like that with lidar and so you're able to create like a much more accurate 3d representation is that correct that's exactly right and the same because we have multiple returns you're not only getting the top of the tree but also the second return is coming from the ground so you get a nice height difference you can calculate the volumes and that same can be said for inspection of rebars or multi-layered stacks of material where photogrammetry can only see the top but lidar can get through that layers and layers of material to give you a nice texture that's amazing why aren't more businesses using lidar on drones right now I mean it's it's a great tool what are some of the reasons that you think that it's not as popular as photogrammetry right now yeah I probably need to work harder you may be making more sales Harris so in short we actually saw four hundred percent growth in the drone applications for lidar since comparing this year versus last year so the market is picking up quickly now because this ecosystem is still maturing we have many companies entering the space I think drone technology is being accepted for the grama tree is being evaluated by many of the large and the price end users I think the next big sensor payload will be lidar and we're working with many players in the market to get there I completely agree with you some of the reasons why I you know I would speculate why it's not as popular is almost drones right now come with a camera on and they don't come with a lidar unit but I think the reason why they don't is cost traditionally it's been higher cost than a small camera size and weight but as you mentioned you know they're the size and weight is coming coming down quite rapidly what are these what could one expect to pay for you know the standard like puck lidar if they wanted to stick one on their m100 or something and start gathering lidar data what kind of cost of entry do we have here sure normally dis surveying and mapping gray light ours are relatively heavier in the kilos of in the low single digit kilograms in terms of weight valid is first-generation lidar as you all know is around seventy to eighty thousand dollars and then over the last year we introduced a puck light and the park park being 830 grams and then the park like is much lighter around 500 less than 600 grams and that is currently going for depending on which model is between eight to ten thousand dollars okay so a significantly cheaper and significantly smaller than from where you guys started out I could see I mean it's just gonna get cheaper cheaper and smaller and smaller as with most technology so I mean I could see a future where yeah i mean like someone like DJ I maybe you know okay it's gotten you know affordable enough for us and there's enough demand out there for people that we're going to start integrating this in to our system so I think you guys are a great candidate for there for that kind of strategy there so we did kind of talk about I kind of take a few steps back just like in the practicality and the use cases of lidar so we're left with specific data outputs so sometimes when we're talking about point clouds just to get a little bit more specific in photogrammetry the file type is typically a dot la s or a dot X Y Z file is that the same type of files that you're kind of working with with lidar data yeah so our raw data is seen with they call it the peak hat and our customers once they complete integration they can output large files so is essentially compatible with data platform companies and how long does it take to process this lidar data like I've heard sometimes that lidar data can just be huge amounts of imagery I mean if you're taking that many measurements every second what kind of file type sizes and what type of like processing times or even processing options does someone have when dealing with lidar yeah that's a great question a comparative photogrammetry light our point cloud definitely is the order of magnitude smaller in terms of size in terms of processing speed as I mentioned earlier with the advancement in mobility processing power on board a drone our customers can actually process that in real time and the word they're using Islam simultaneous localization and mapping or they can actually generate a 3d model real time for both inspection and also collision avoidance functions hmm so what so it could it's not going to be just yeah grabbing data and for processing it's also going to be the collision avoidance I mean it's going to be like a 360-degree coverage of what Ariel you know these vehicles really need are you guys I'm assuming you already are but are you investigating some of this like detect and avoid and sense and avoid technology with with your lidar technology velodyne or are you more focused on the data collection aspect yeah I think to use a on board a mainstream drone today because it's around a thousand to two thousand dollars so using a light are currently is still I like more expensive than the drone itself for pure collision avoidance might be overkill hmmm but for industrial applications where the environment is very complex and the risk the risk and the failure cost is much higher than it makes sense to use a fairly robust sensor to make sure the drone does not crash into anything and I think based on our market research the major hurdle to increase drone the option is the operator today requires a lot of experience to make sure you do not crash a hundred-thousand-dollar equipment I think having this technology will help us really putting the you into the UAV where it's really autonomous young man vehicle I like that so you can start I think yeah you will start seeing you see DJ I using a lot of this vision just computer vision to detect things but when you combine the vision with the lidar data I mean I think you already see that on autonomous land vehicles it's just gonna it's just going to go and grow wings basically and then and then come up to us in the air so that's going to be really interesting well should we start seeing that I mean it'll just be so much more accurate range will increase a lot safer which is the bottom line for some of these industrial companies speaking of that what are some of your favorite use cases that you've seen or maybe stories of somebody using lidar to accomplish a specific task from it from a drone yeah I will say refer to the three main use cases mapping inspection passive mode active mode is the real time processing of the data and then hopefully we'll have autonomous flight applications for drone delivery soon I will say the most interesting I've witnessed together with my colleague in Germany was a full autonomous inspection of a wind turbine where the the system is using our Park light to track where the drill is versus the turbine blade and make sure the pictures are taken consistently so now you have repeatability and zero risk for the operator as you know the wind turbines are very high could be a very dangerous drop job to climb up and take pictures before by hand and it would be very very tough to try to repeat the same flight with manual control of the drone to given the wind and everything I mean the autonomous aspect can just be so much more consistent so that's great yeah it's all about consistency consistency is key with all these inspections to repeat and repeat and do it you know in different environments times a day etc that's really cool so what are you excited what are you most excited about for the future of velodyne and lidar with drones I mean what are you kind of waiting for or anticipating as somebody who's really on the forefront of all this technology yeah so no though I think autonomous driving is really happening it will be here in the next three to five years and I think for you and I to buy autonomous car probably will happen within the next within ten years now for the drones we do believe because the product development cycle is much quicker as regulations improve globally we potentially could see more drones autonomously flying even before you and i can buy autonomous car mmm nice that's a cool future so awesome well harris thank you so much for joining us you can actually follow velodyne the company on twitter at velodyne lidar that's ve l 0 dy and e li dar and you can visit their website at velodyne lidar calm and Harris has been gracious enough you can actually email him directly if you have any questions maybe you want to investigate this technology a little bit more and see how you can integrate it on your commercial drone operations ping him at Harris har our is Wang w ang at velodyne calm so again thank you so much for joining us Harris it was a real pleasure there's so much more to learn I'll definitely be keeping an eye a very close eye on what you guys are up to and pointing more people over to the benefits of lidar but again it's just you've got to find what the best tool for the job is so really appreciate your time thanks for being here thank you in alright guys we're gonna go ahead and cut off the mics cheers
LiDAR is an impressive and interesting sensor technology which already powers parts of the driverless car industry. LiDAR sensors can somewhat be thought of as a clever mixture of photogrammetry and radar. It is extremely precise and can provide incredibly accurate datasets. Harris Wang, Strategic Markets Director at Velodyne LiDAR Inc., joins Ian to explore how LiDAR is being used on drones. Industries like utilities, surveying, forestry, and inspection can reap insane benefits by using LiDAR—but it has historically been quite heavy and very expensive. Harris explains how the technology is becoming cheaper and smaller, how LiDAR compares to photogrammetry, and how it is being used today and in the future.
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