Agile-legged robots have proven to be highly effective in navigating and performing tasks in complex and challenging environments, including disaster zones and industrial settings. However, these applications normally require the capability of carrying heavy loads while maintaining dynamic motion. Therefore, this paper presents a novel methodology for incorporating adaptive control into a force-based control system. Recent advancements in the control of quadruped robots show that force control can effectively realize dynamic locomotion over rough terrain. By integrating adaptive control into the force-based controller, our proposed approach can maintain the advantages of the baseline framework while adapting to significant model uncertainties and unknown terrain impact models. Experimental validation was successfully conducted on the Unitree A1 robot. With our approach, the robot can carry heavy loads (up to 50% of its weight) while performing dynamic gaits such as fast trotting and bounding across uneven terrains.

翻译：敏捷腿式机器人在复杂和挑战性环境（包括灾区及工业场景）中的导航与任务执行中展现出极高有效性。然而，这些应用通常要求机器人在保持动态运动的同时具备重载能力。为此，本文提出一种将自适应控制集成至基于力控制系统的新颖方法。四足机器人控制的最新进展表明，力控制可有效实现粗糙地形上的动态运动。通过将自适应控制融入基于力的控制器，我们提出的方法能在保留基础框架优势的同时，适应显著模型不确定性及未知地形冲击模型。实验验证在宇树A1机器人上成功完成。采用该方法，机器人可在执行快速小跑及跨越不平整地形等动态步态时，承载高达自身重量50%的重负荷。