Robotic Research Secures $228M Series A Funding

Robotic Research Secures $228 Million in Series A Funding

Robotic Research, a company specializing in self-driving technology, has successfully closed a $228 million Series A funding round. For two decades, they have focused on developing autonomous vehicles for both on and off-road use, primarily for the Department of Defense.

The investment was spearheaded by SoftBank Vision Fund 2 and Enlightenment Capital. These funds will be strategically allocated to expand the company’s commercial operations.

Investment Participants and Current Deployments

Crescent Cove Advisors, Henry Crown and Company, and Luminar, a prominent lidar technology firm, also contributed to this funding round.

Currently, Robotic Research, operating under the brand RR.AI, has deployed its vehicle-agnostic AutoDrive autonomy kits in approximately 150 heavy-duty vehicles. These include transit buses, Class 8 trucks, and yard trucks, operating across the United States, Canada, Australia, Europe, and Saudi Arabia, as stated by CEO Alberto Lacaze.

Unique Capabilities and Competitive Advantages

Historically, Robotic Research has concentrated on automating trucks for the U.S. Army and Navy. These vehicles operate in challenging environments lacking mapped data, reliable GPS signals, consistent communications, or clearly marked roads.

The company’s autonomy system incorporates sensors not typically found in commercial autonomous vehicles. These include stereo vision and structure from motion, a technique for creating 3D models from 2D images, according to Lacaze. This gives RR.AI a distinct advantage over competitors hesitant to operate in adverse weather conditions.

The "Stamp Collection" Approach to Robotics

“Robotics isn’t simply about sophisticated software,” Lacaze explained to TechCrunch. “It’s more akin to collecting diverse scenarios. You must be prepared for conditions like slippery roads, dust, and the absence of lane markings.”

He further elaborated that Robotic Research has amassed a substantial collection of these “stamps,” meaning they’ve encountered and solved a wide range of challenging operational situations. Military applications often present the most demanding edge cases, which translate well to commercial environments.

Focus on Commercial Expansion and Industrialization

Given the broad deployment of its technology, the recent funding is specifically intended to accelerate the expansion and industrialization of commercial applications, Lacaze confirmed.

Last year, Robotic Research secured a contract with the Connecticut Department of Transportation. This project involves automating three 40-foot electric buses on the CTfastrak corridor, with plans to extend this to a full bus rapid transit line, bus platooning, and precise docking procedures.

These buses operate at Level 4 autonomy, meaning they don’t require human intervention under specific conditions, but will still have safety drivers on board, as defined by SAE standards.

Partnerships and Future Announcements

In the trucking sector, RR.AI is collaborating with sawmills in Canada to automate log transport. A significant announcement regarding U.S. operations is also forthcoming.

Furthermore, the company anticipates announcing a partnership within the agricultural industry in the coming months.

Strategic Go-to-Market Approach

RR.AI’s market entry strategy centers on targeting “low-hanging fruits” – areas with minimal or easily navigated regulations, according to Lacaze.

“Our priority is to operate where we can effectively utilize current sensor technology at existing costs and generate profitability,” Lacaze stated. He noted that sensors like cameras, lidar, and radar remain expensive, making them more cost-effective for larger, heavy-duty vehicles with longer lifespans.

Profitability and Rapid Growth

“We are uniquely positioned in the autonomy space as a consistently profitable company since our inception,” Lacaze emphasized. “This is due to our focus on niche markets that provide immediate revenue streams.”

This approach allows RR.AI to avoid waiting until 2025 for widespread truck deployment, enabling faster growth and data collection.

Future Considerations and Vehicle Availability

While operating in robotaxis remains a possibility for RR.AI, Lacaze indicated the company will await improvements in the regulatory landscape and reductions in sensor costs before entering that vertical.

However, a potential challenge lies in the availability of vehicles. “We rely on vehicle manufacturers for production, as we do not build our own vehicles,” Lacaze explained. “We are actively seeking vehicles in regions where deployment is currently feasible from a regulatory perspective.”