Agile and Safe Trajectory Planning for Quadruped Navigation with Motion Anisotropy Awareness

Quadruped robots demonstrate robust and ag- ile movements in various terrains; however, their naviga- tion autonomy is still insufficient. One of the challenges is that the motion capabilities of the quadruped robot are anisotropic along different directions, which significantly af- fects the safety of quadruped robot navigation. This paper proposes a navigation framework that takes into account the motion anisotropy of quadruped robots including kinodynamic trajectory generation, nonlinear trajectory optimization, and nonlinear model predictive control. In simulation and real robot tests, we demonstrate that our motion-anisotropy-aware navigation framework could: (1) generate more efficient trajec- tories and realize more agile quadruped navigation; (2) signif- icantly improve the navigation safety in challenging scenarios. The implementation is realized as an open-source package at https://github.com/ZWT006/agile navigation.