  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.
