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

Quadruped robots demonstrate robust and agile movements in various terrains; however, their navigation autonomy is still insufficient. One of the challenges is that the motion capabilities of the quadruped robot are anisotropic along different directions, which significantly affects 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 trajectories and realize more agile quadruped navigation; (2) significantly improve the navigation safety in challenging scenarios. The implementation is realized as an open-source package at https://github.com/ZWT006/agile_navigation.

I. INTRODUCTION

A quadruped robot is a bionic machine mimicking the locomotion of quadruped animals in nature. It is capable of omnidirectional movement and traversing complex terrains. Recent advancements in locomotion control for quadruped robots include model predictive control (MPC) [1]–[5] and learning-based approaches [6]–[10]. These works demonstrate the stable and agile locomotion over various terrains where the reference trajectory to be tracked is given by the user command.