Rigid body dynamics is a key 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 RBDCore, to address the performance bottleneck. By analyzing different functions commonly used in robot dynamics calculations, we summarize their reuse relationship and optimize them according to the hardware. Based on this, RBDCore can fully reuse common hardware modules when processing different computing tasks. By dynamically switching the dataflow path, RBDCore can accelerate various dynamics functions without reconfiguring the hardware. We design Structure-Adaptive Pipelines for RBDCore, 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, RBDCore can significantly improve the performance.

翻译：刚体动力学是机器人领域的关键技术。在轨迹优化和模型预测控制算法中，通常包含大量刚体动力学计算任务。使用CPU处理这些任务会消耗大量时间，进而影响机器人的实时性能。为此，我们提出了一种名为RBDCore的多功能机器人刚体动力学加速器，以解决性能瓶颈。通过分析机器人动力学计算中常用的不同函数，我们总结了它们的复用关系，并根据硬件进行了优化。基于此，RBDCore在处理不同计算任务时能够充分复用通用硬件模块。通过动态切换数据流路径，RBDCore无需重新配置硬件即可加速多种动力学函数。我们为RBDCore设计了结构自适应流水线，可大幅提升加速器的吞吐量。具有不同结构和参数的机器人均可得到针对性的优化。与当前最先进的CPU、GPU动力学库以及FPGA加速器相比，RBDCore能显著提升性能。