Washington: The Marine Corps has awarded Forterra a contract to integrate its autonomy package on the Remotely Operated Ground Unit for Expeditionary (ROGUE) Fires ground vehicle, the Pentagon’s first-ever production contract for off-road autonomous driving capability.
The company’s advanced stack and AutoDrive system gives the ROGUE Fires vehicle – built by Oshkosh Defence – off-road, self-driving technology in “nearly any environment,” which moves “beyond Leader-Follower capabilities,” Forterra said in a January 13 statement. Leader-Follower technology uses a lead vehicle to guide other unmanned vehicles behind it.
The deal to integrate the technology comes after two ROGUE Fires Low-Rate Initial Production orders in fiscal 2025.
“By seamlessly integrating cutting-edge autonomous technologies with Oshkosh systems, we’re equipping the Marine Corps to strengthen sea denial capabilities, enhance operational agility, and maintain a decisive technological edge against evolving threats,” Pat Williams, Oshkosh Defence chief programs officer, said in the statement.
The Marines first awarded Oshkosh a contract to produce the unmanned missile launcher after a prototyping phase in September 2023 for $40 million.
The ROGUE Fires design removes the cab of the Oshkosh-made Joint Light Tactical Vehicle and tacks on a missile launcher that can be remotely fired. The Marine Corps paired the ROGUE Fires system with the Naval Strike Missile to create the Navy/Marine Expeditionary Ship Interdiction System, or NMESIS. Oshkosh has said ROGUE Fires is payload agnostic.
Forterra is one of three companies also working directly with the Army’s Next-Generation Combat Vehicle Cross Functional Team and Program Executive Office Ground Combat Systems on autonomy capability along with Kodiak Robotics and Overland AI.
So far, the evaluations for autonomous behaviour haven’t even been truly off-road, Maj Gen Glenn Dean, program executive officer for GCS, said last fall. “We’re talking trails and unimproved road conditions. Building an autonomy algorithm that can identify the entire range of things it might encounter is challenging because you have a pretty big data set.”
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