具备运动各向异性意识的四足机器人导航轨迹规划
Agile and Safe Trajectory Planning for Quadruped Navigation with Motion Anisotropy Awareness
AI总结：
本文提出了一种考虑四足机器人运动各向异性的导航框架，通过轨迹生成与优化提升导航效率和安全性。
摘要：
四足机器人在各种地形上表现出稳健和敏捷的运动能力；然而，其导航自主性仍然不足。其中一个挑战是四足机器人的运动能力在不同方向上是各向异性的，这显著影响了四足机器人导航的安全性。本文提出了一种导航框架，该框架考虑了四足机器人运动各向异性，包括运动动力学轨迹生成、非线性轨迹优化和非线性模型预测控制。在仿真和真实机器人测试中，我们证明了我们的运动各向异性意识导航框架能够：（1）生成更高效的轨迹并实现更敏捷的四足机器人导航；（2）在具有挑战性的场景中显著提高导航安全性。该实现作为开源包发布在https://github.com/ZWT006/agile_navigation。
英文摘要：
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.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
