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：敏捷腿式机器人已被证明在复杂和具有挑战性的环境中（包括灾区与工业场景）进行导航和任务执行时具有高效性。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融入基于力控系统的创新方法。四足机器人控制的最新进展表明，力控能够有效实现粗糙地形上的动态运动。通过将自适应控制集成到基于力控的控制器中，本方法可在保持基础框架优势的同时，适应显著的模型不确定性和未知的地形冲击模型。实验验证已在Unitree A1机器人上成功实施。采用本方法后，机器人可在承载高达其体重50%重物的条件下，执行如快速小跑和跳跃等动态步态，穿越不平坦地形。