Recently Brianna Wessling sat down with Duality AI co-founders Apurva Shah and Mike Taylor. The article was published on September 12, 2024, and you can read the full version at The Robot Report.
By Brianna Wessling | September 12, 2024
For robots to truly be able to navigate in the real world, the software that powers them needs to be reliable enough to enter any environment and accurately navigate. Otherwise, you’re left with a robot that needs to be reprogrammed when it goes from a forest to a field of grass. This is the kind of work Duality AI is doing in its new agreement with NASA’s Jet Propulsion Laboratory, or JPL, in Pasadena, Calif.
The San Mateo, Calif.-based company today said it will continue its work on the Defense Advanced Research Projects Agency (DARPA) Robotic Autonomy in Complex Environments with Resiliency (RACER) program.
This announcement followed Phase 1 of the RACER project, which Duality completed as one of only two simulation providers selected by DARPA. The company said this latest agreement accelerates development of autonomy for NASA JPL by allowing rapid iteration and discovery of flaws through simulation and reducing risks. It will also provide the synthetic data vital to training advanced AI algorithms that push the boundaries of robotic autonomy.
“For Phase 1, we were actually part of RACER Sim,” Michael Taylor, Duality’s chief product officer, told The Robot Report. “So RACER Sim was a sister effort. We were a prime, and the other team was led by Intel. RACER Sim was envisioned to push forward the state of the art for simulation technologies for building off-road robots. DARPA recognized the gaps there.”
During the second phase of the RACER program, teams must demonstrate their ability to create advanced AI systems that allow large-scale vehicles to travel autonomously at faster speeds and over longer distances than in Phase 1.
The team from NASA JPL will use Duality’s advanced digital twin simulator, Falcon, to overcome the challenges associated with autonomous high-speed, off-road vehicles, including mapping, perception, planning, and responding to hazards and obstacles.
READ THE FULL ARTICLE AT THE ROBOT REPORT.