让四足机器人在未知行星地形中自主行走，自适应调整步态和控制。
An adaptive hierarchical control framework for quadrupedal robots in planetary exploration
- 分层控制框架融合动态建模与在线参数自适应。
- 实测在火山地貌行走超700米，支持多种硬件平台。
- 开源集成于ROS 2，适合深空探测机器人研发者。
行星探索任务需要能在极端未知环境中导航的机器人。尽管轮式漫游车曾主导以往任务，但其仅限于可通行表面。腿式机器人，尤其是四足机器人，能应对不平、障碍密集和可变形地形。然而，在地形与机器人参数不确定的情况下，部署此类机器人面临挑战，因需依赖环境特异性控制。本文提出一种模块化控制框架，结合基于模型的动力学控制、在线模型自适应与自适应步态规划，以应对机器人和地形属性的不确定性。该框架包含无接触传感与有接触传感下的状态估计，支持运行时重构，并已集成至ROS 2，开源可用。其性能在两个四足平台、多种硬件架构及火山地貌测试中得到验证，机器人成功行走超过700米。
原文摘要 · Abstract (English)
Planetary exploration missions require robots capable of navigating extreme and unknown environments. While wheeled rovers have dominated past missions, their mobility is limited to traversable surfaces. Legged robots, especially quadrupeds, can overcome these limitations by handling uneven, obstacle-rich, and deformable terrains. However, deploying such robots in unknown conditions is challenging due to the need for environment-specific control, which is infeasible when terrain and robot parameters are uncertain. This work presents a modular control framework that combines model-based dynamic control with online model adaptation and adaptive footstep planning to address uncertainties in both robot and terrain properties. The framework includes state estimation for quadrupeds with and without contact sensing, supports runtime reconfiguration, and is integrated into ROS 2 with open-source availability. Its performance was validated on two quadruped platforms, multiple hardware architectures, and in a volcano field test, where the robot walked over 700 m.
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