DARPAtv | RACER Experiment 4 - Cockpit view of an autonomous off-road run in TX @DARPAtv | Uploaded April 2024 | Updated October 2024, 4 days ago.
DARPA’s Robotic Autonomy in Complex Environments with Resiliency (RACER) program recently conducted its fourth experiment (E4) to assess the performance of off-road unmanned vehicles. At these tests, conducted in Texas in late 2023, teams successfully completed over 30 autonomous runs on courses varying from 3 to 10 miles in length, achieving over 150 autonomous, unoccupied miles at speeds up to 30 miles per hour.
This video shows a cockpit perspective of a RACER Fleet Vehicle (RFV) in an autonomous run successfully negotiating ditches and vegetation at speed.
These tests -- which also incorporated a larger RACER Heavy Vehicle -- are the start of Phase 2 of the RACER program; performer teams are the University of Washington and Overland AI; and NASA’s Jet Propulsion Laboratory, Offroad Autonomy, Georgia Institute of Technology, and Duality Robotics.
Using the algorithms on a two very different platform helps RACER toward its goal of platform agnostic autonomy of combat-scale vehicles in complex, mission-relevant off-road environments that are significantly more unpredictable than on-road conditions.
DARPA’s Robotic Autonomy in Complex Environments with Resiliency (RACER) program recently conducted its fourth experiment (E4) to assess the performance of off-road unmanned vehicles. At these tests, conducted in Texas in late 2023, teams successfully completed over 30 autonomous runs on courses varying from 3 to 10 miles in length, achieving over 150 autonomous, unoccupied miles at speeds up to 30 miles per hour.
This video shows a cockpit perspective of a RACER Fleet Vehicle (RFV) in an autonomous run successfully negotiating ditches and vegetation at speed.
These tests -- which also incorporated a larger RACER Heavy Vehicle -- are the start of Phase 2 of the RACER program; performer teams are the University of Washington and Overland AI; and NASA’s Jet Propulsion Laboratory, Offroad Autonomy, Georgia Institute of Technology, and Duality Robotics.
Using the algorithms on a two very different platform helps RACER toward its goal of platform agnostic autonomy of combat-scale vehicles in complex, mission-relevant off-road environments that are significantly more unpredictable than on-road conditions.
