Dadu-RBD: Robot Rigid Body Dynamics Accelerator with Multifunctional Pipelines
Yuxin Yang, Xiaoming Chen, Yinhe Han · 2023
Rigid body dynamics is a core technology in the robotics field. In trajectory optimization and model predictive control algorithms, there are usually a large number of rigid body dynamics computing tasks. Using CPUs to process these tasks consumes a lot of time, which will affect the real-time performance of robots. To this end, we propose a multifunctional robot rigid body dynamics accelerator, named Dadu-RBD, to address the performance bottleneck. By analyzing different functions commonly used in robot dynamics calculations, we summarize their relationships and characteristics, then optimize them according to the hardware. Based on this, Dadu-RBD can fully reuse common hardware modules when processing different computing tasks. By dynamically switching the dataflow path, Dadu-RBD can accelerate various dynamics functions without reconfiguring the hardware. We design the Round-Trip Pipeline and Structure-Adaptive Pipelines for Dadu-RBD, which can greatly improve the throughput of the accelerator. Robots with different structures and parameters can be optimized specifically. Compared with the state-of-the-art CPU, GPU dynamics libraries and FPGA accelerator, Dadu-RBD can significantly improve the performance.