A new crop of early-stage startups — along with some recent VC investment — illustrates an emerging niche in autonomous vehicle technology. Unlike companies bringing robotaxis to city streets, these startups are taking their technology off-road.
Two recent entrants — based in Seattle Overland AI and based in New Brunswick Potential — are poised to gain a first-mover advantage in this stretch of autonomy.
While these startups apply their technology in different ways, Overland AI and Potential share something in common off-road. The founders of each startup believe they have cracked the code on one of the most challenging applications of automated driving, creating software that does not rely on some of the main crutches of testing and development — such as detailed maps, large amounts of training data, and the ability to return to remote assistance.
The US Department of Defense and venture capitalists are taking note.
Overland AI, which is developing an autonomous driving system designed for military operations such as reconnaissance, surveillance and electronic warfare package delivery, was awarded in April to 18.6 million dollars by the US Army’s Defense Innovation Unit. The funds will be used to build a prototype autonomous software stack for the Robotic Combat Vehicle (RCV) program over the next two years.
The startup, which was founded in 2022, this week raised a $10 million seed round led by Point72 Ventures. The funds will be used to expand Overland’s team and continue development of OverDrive, the company’s autonomy stack, according to CEO and founder Byron Boots.
Meanwhile, Potential, which makes advanced driver assistance systems (ADAS) that enable ATVs, underground mining vehicles and passenger cars to handle off-road environments, has raised a $2M CAD (~US$1.5M) expansion ) in the seed round of Brightspark Ventures, a Canadian early-stage VC. This brings Potential’s total funding to $8.5 million CAD (~$6.2 million USD). The startup has spent the last six years developing its technology and is now doing several pilot projects in power sports, motorcycles and cars.
Off road opportunity
Potential and Overland AI aren’t the only companies trying to apply autonomous vehicle technology to areas off public roads. The high-cost pursuit of commercial robotaxis and self-driving trucks has stymied dozens of startups in recent years. As those have shut down, a new batch of startups like Polymath Robotics, Forterra, Pronto.ai, Bear Robotics and Outrider have emerged with more grounded ambitions: applying AV technology to warehouse, mining, industrial and off-road environments.
“We’re absolutely capitalizing on off-road autonomy,” Alexei Andreev, CEO of Autotech Ventures, told TechCrunch. “In fact, if anything, we stay away from the highway range and completely double the off-road range.”
Most of the off-road companies Autotech Ventures invests in today are in the agriculture and construction sectors — products like autonomous mining vehicles, forklifts and tractors. Andreev says that for these sectors, it’s about addressing labor shortages while increasing productivity and making farms and construction sites safer.
“And if you remove people, you’ll immediately have a reduction in your premiums. So the ROI for these vertical applications is now and it’s significant,” Andreev said.
Another result: Off-road autonomy has found a friend in defense.
Overland AI: From DARPA to Startup Funding
When it comes to automating off-road driving, the US military might be a great customer. After all, autonomous vehicles started as a DARPA project, says Jeff Peters, a partner at Ibex Investors. DARPA (Defense Advanced Research Projects Agency) is an agency of the US Department of Defense focused on advancing technology for military use.
“The hype around AV has driven the industry a lot toward larger potential commercial applications, but the DoD projects have continued,” Peters told TechCrunch via email, noting that autonomous mining startup SafeAI and autonomous trucking startup Kodiak Robotics they have also sought defense grants. “I think the AV companies (those still around) will go after DoD projects because it offers great, unrestricted funding in the interim before commercial activities.”
Overland AI is the latest byproduct of the DARPA program. Boots, a professor of machine learning at the University of Washington and founder of the Robot Learning Laboratory in the university’s school of computer science and engineering, has a long history of collaboration with the US Army Research Laboratory and DARPA.
The Overland grew out of Boots’ research and team participating in DARPA’s RACER (Robotic Autonomy in Complex Environments with Resiliency) program, which aims to develop self-driving vehicles that can handle rough terrain.
The program is still ongoing. Overland, which is filled with deep-tech veterans from Google, Nvidia, Apple, Waymo, Aurora, Embark and Argo as well as software engineers who have worked on mission-critical solutions at SpaceX, RTX and the US Army, was recently selected to proceed to the second phase.
“The high-level idea is that right now almost every ground vehicle that the military uses has a person in it,” Botch told TechCrunch in a video interview. “And you can imagine if you can just pull the person out of the vehicle, that offers safety and tactical advantages.”
To pull it off means vehicles need to autonomously navigate complex off-road terrain using only on-board sensors (mainly cameras, according to Boots) and calculate, without relying on maps, GPS or remote operators. That means Overland’s software must understand the geometry of the terrain — including things like vegetation and mud — every step of the way and how that affects the vehicle’s dynamics.
“The terrain dictates how the vehicle moves,” Botch said.
Overland’s technology “basically takes sensor data and creates a terrain representation as it goes,” Boots explained. The vehicle then uses that digital representation “plus the target it’s trying to reach, which could be several kilometers away, to try to find a path through the terrain to that target.”
“Part of the advantage of having an autonomous system is that when the system is tasked, if you lose a communication link with that ground vehicle, it will continue to move towards its target and try to complete the task until the communication link is re-established .” said Botts.
Most road driving today relies on this remotely assisted telecommunications connection, in part because the risk to other road users is higher. That’s why you’ll see Waymo and Cruise robotaxis off the streets of San Francisco, waiting for a remote operator to give them a boost after they’ve stopped driving to meet a minimum safety requirement.
“Military ground systems often need to operate in unstructured, dynamic terrain. We believe that self-driving technology built for well-defined roads and closed spaces will struggle there, and that it takes a very strong team to deliver functionally relevant terrain autonomy in these environments,” Chris Morales, partner in the defense technology team at Point72 Ventures , he told TechCrunch.
Capabilities with ADAS off-road
“How do you really allow someone who is maybe not a 100% experienced driver, but someone who wants to go off-road and experience these more difficult conditions?” Sam Poirier, CEO of Potential, asked in a recent interview.
Potential’s core platform, called Terrain Intelligence, uses computer vision to help vehicles see, interpret and prepare for complex terrain and changing surface conditions ahead. Terrain Intelligence can read data from a single camera, rather than relying on additional sensors such as additional cameras, lidar and radar.
At its most basic level, Potential’s off-road ADAS alerts the driver to an impassable object ahead or the need to change to a better driving setting based on new terrain.
“The second layer is, can we instead help automate settings changes that are usually wizard-assisted?” Poirier said. “Most vehicles have two-wheel drive, four-wheel drive, sand mode, mud mode, things like that. Ultimately, at this stage, it is up to the driver to switch between them… and the driver needs to understand when to use these different functions.”
The final level of potential will involve using existing sensor data and fine-tuning these settings and pushing performance limits.
“There are things that assistive tools can do that an individual driver — no matter how experienced you are — can’t do on their own,” said Scott Kunselman, a former chief engineer at Jeep, an automotive veteran and consultant to Potential. “Stability controls are a good example because to activate stability control, you need independent brake control. The driver has only one brake pedal and activates the entire braking system simultaneously. Whereas stability control can activate each wheel individually so you can create, for example, the ability to compensate for yaw in a vehicle.”
Yaw, by the way, is when a vehicle’s weight shifts from its center of gravity to the right or left, which can cause it to shimmy outward or fish.
Potential said it works with both Tier 1 suppliers and OEMs to license its software and integrate it directly into vehicles. Andreev suggests a possible focus on business relationships with Tier 1 suppliers instead of OEMs who are less likely to take a chance on a small startup.
