Presentation
Energy-Efficient, Real-Time Robotic Path Planning through FPGA Acceleration
DescriptionReal-world path planning for Autonomous Mobile Robots (AMR) requires the ability to navigate safely and efficiently in stochastic environments. At the same time, AMRs face stringent power limitations. As such, fast and efficient motion and path-planning solvers are needed at the edge to enable the required long-duration performance of next-generation robotic systems. In this work, we explore the potential of hardware acceleration on Field Programmable Gate Arrays (FPGAs) to achieve this dual performance requirement, targeting the state-of-the-art sampling-based motion planning algorithm, Model Predictive Path Integral (MPPI). Our preliminary results indicate that FPGAs can provide both improved runtimes—up to 68% and 82%—and more energy-efficient operation—up to 74% and 49%—than GPUs and CPUs respectively, paving the way for future robotic applications.
Event Type
Networking
Work-in-Progress Poster
TimeMonday, June 236:00pm - 7:00pm PDT
LocationLevel 2 Lobby