Two-layer adaptive trajectory tracking controller for quadruped robots on slippery terrains

Quadruped robots are commonly employed in challenging and unpredictable environments where their stability and controllability could be compromised during locomotion. During task execution, the robot might face non-controllable conditions or loss of balance either due to dynamic contact events or aggressive control efforts, e.g. during trajectory tracking. In this work, we propose a robust adaptive trajectory tracking controller that consists of two prioritized layers of adaptation aimed at maintaining stability during dynamic (possibly unstable) contact of one or more supporting legs. The aforementioned key-feature can serve as the basis for avoiding slippage during dynamic locomotion. The proposed method is a novel lightweight analytical solution that assumes no prior knowledge of the friction properties of the surface. This is accomplished by considering the slippage probability as extracted by our previous work on contact state estimation in order to avoid non-controllable conditions. We evaluate our approach through simulations and validate it with real experiments, demonstrating robustness in multiple scenarios.