  Adaptive control can address model uncertainty in control systems. However,
it is preliminarily designed for tracking control. Recent advancements in the
control of quadruped robots show that force control can effectively realize
agile and robust locomotion. In this paper, we present a novel adaptive
force-based control framework for legged robots. We introduce a new
architecture in our proposed approach to incorporate adaptive control into
quadratic programming (QP) force control. Since our approach is based on force
control, it also retains the advantages of the baseline framework, such as
robustness to uneven terrain, controllable friction constraints, or soft
impacts. Our method is successfully validated in both simulation and hardware
experiments. While the baseline QP control has shown a significant degradation
in the body tracking error with a small load, our proposed adaptive force-based
control can enable the 12-kg Unitree A1 robot to walk on rough terrains while
carrying a heavy load of up to 6 kg (50% of the robot weight). When standing
with four legs, our proposed adaptive control can even allow the robot to carry
up to 11 kg of load (92% of the robot weight) with less than 5-cm tracking
error in the robot height.

Robotics;Systems and Control;Systems and Control