April 26, 2022 — DARPA, the Defense Advanced Research Projects Agency, has awarded Intel Federal LLC a contract to develop advanced simulation solutions for off-road autonomous ground vehicles. The company said Intel Labs will work in partnership with its collaborators, the Computer Vision Center Barcelona, and the University of Texas at Austin.
The RACER-Sim (Robotic Autonomy in Complex Environments with Resiliency – Simulation) program aims to create off-road simulation platforms to reduce the development cost and bridge the gap between simulation and the real world.
RACER-Sim includes two phases over 48 months aimed at accelerating R&D for designing off-road autonomous vehicles. In phase one, Intel said it will focus on create new simulation platforms and map generation tools that mimic off-road environments, e.g., physics, sensor modeling, terrain complexity, etc., at scale, a process, Intel said, that traditionally requires significant resources and is one of the biggest challenges in simulation workflows. The company said Intel Labs’ simulation platform will enable customization of future maps, including the creation of new environments covering more than 100,000 square miles, with a few clicks.
In phase two, Intel Labs will work with RACER collaborators to implement new algorithms without the use of a physical robot. Then, teams will validate the performance of the robot in simulation with the intent of saving time and resources. Phase two will also include the development of new sim2real techniques – the concept of training the robot in simulation to acquire skills and then transferring these skills to a corresponding real robotic system – the aim to enable training of off-road autonomous ground vehicles directly in simulation.
“Intel expects these new simulation tools to significantly improve the development of autonomous systems using virtual testing, which reduces the risks, costs, and delays associated with traditional testing and verification protocols,” the company said. “In the future, the simulation platform will go beyond validation to create AI models ready for implementation in the real world.”
“Intel Labs has already made progress in advancing autonomous vehicle simulation through several projects, including the CARLA simulator, and we’re proud to participate in RACER-Sim to continue contributing to the next frontier of off-road robotics and autonomous vehicles,” said German Ros, Autonomous Agents Lab director at Intel Labs. “We brought together a team of renowned experts from the Computer Vision Center and UT Austin with the goal of creating a versatile and open platform to accelerate progress in off-road ground robots for all types of environments and conditions.”
Intel said the gap between autonomous on-road and off-road deployment is significant. Many simulation environments exist today, but few are optimized for off-road autonomy development at scale and speed. Additionally, real-world demonstrations continue to serve as the primary method to verify system performance, according to the company. Off-road autonomous vehicles must deal with a range of challenges, including a lack of road networks and extreme terrain with rocks and all types of vegetation, among many others. Such extreme conditions make developing and testing expensive and slow. The RACER-Sim program aims to solve this problem by providing advanced simulation technologies to develop and test solutions, reducing deployment time and validation of AI-powered autonomous systems.
