Unknown Payload Adaptive Control for Quadruped Locomotion With Proprioceptive Linear Legs

Quadruped robots manifest great potential to traverse rough terrains with payload. Current model-based controllers, which are extensively adopted in quadruped robot locomotion control, rely on accurate estimation of parameters and will significantly deteriorate in severe disturbance, e.g., adding heavy payload. This article introduces an online identification method, which is named as adaptive control for quadruped locomotion, to address model uncertainties. Meanwhile, a concurrent adaptive controller is also indispensable to accomplish identification and locomotion. Therefore, this article presents an adaptive control algorithm based on the online payload identification for the high payload capacity (the ratio between payload and robot's self-weight) quadruped locomotion. The newly proposed algorithm could achieve estimating and compensating the external disturbances induced by the payload online. The tracking accuracy of the robot's center of mass and orientation trajectories for the identification task is highly improved. The locomotion task can be incorporated in inverse-dynamics-based quadratic programming, realizing a trotting gait. The proposed method is verified in a real quadruped robot platform. Experiments prove the estimation efficacy for the payload weighing from 20 to 75 $\rm kg$ and loaded at different locations of the robot's torso.