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

Fuente: arXiv
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Autori principali: Zhang, Wentao, Xu, Shaohang, Cai, Peiyuan, Zhu, Lijun
Natura: Preprint
Pubblicazione: 2024
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author Zhang, Wentao
Xu, Shaohang
Cai, Peiyuan
Zhu, Lijun
author_facet Zhang, Wentao
Xu, Shaohang
Cai, Peiyuan
Zhu, Lijun
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2403_10101
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Agile and Safe Trajectory Planning for Quadruped Navigation with Motion Anisotropy Awareness
Zhang, Wentao
Xu, Shaohang
Cai, Peiyuan
Zhu, Lijun
Robotics
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.
title Agile and Safe Trajectory Planning for Quadruped Navigation with Motion Anisotropy Awareness
topic Robotics
url https://arxiv.org/abs/2403.10101