RISK AWARE AUTONOMOUS VEHICLES
The power of Realtime's motion planning processor enables autonomous vehicles to calculate probabilistic outcomes of various driving choices in the midst of complex arrays of actors in urban driving, enabling safe choices at normal driving speeds, easing adoption of this lifesaving technology
Academic paper: ROBOT MOTION PLANNING ON A CHIP
We describe a process that constructs robot-specific circuitry for motion planning, capable of generating motion plans approximately three orders of magnitude faster than existing methods. Our method is based on building collision detection circuits for a probabilistic roadmap. Collision detection for the roadmap edges is completely parallelized, so that the time to determine which edges are in collision is independent of the number of edges. We demonstrate planning using a 6-degreeof-freedom robot arm in less than 1 millisecond.
Academic Paper: THE MICROARCHITECTURE OF A REAL-TIME ROBOT MOTION PLANNING ACCELERATOR
Abstract—We have developed a hardware accelerator for motion planning, a critical operation in robotics. In this paper, we present the microarchitecture of our accelerator and describe a prototype implementation on an FPGA. We experimentally show that the accelerator improves performance by three orders of magnitude and improves power consumption by more than one order of magnitude. These gains are achieved through careful hardware/software co-design. We modify conventional motion planning algorithms to aggressively precompute collision data, as well as implement a microarchitecture that leverages the parallelism present in the problem.