Fuzzy approximation adaptive control of quadruped robots with kinematics and dynamics uncertainties

This paper investigates optimal feet forces distribution and control of quadruped robots with uncertainties in both kinematics and dynamics. First, a constrained dynamics of quadruped robots is established. The distribution of required forces and moments on the supporting legs of a quadruped robot can be formulated as a problem for minimizing an objective function subject to form-closure constraints and balance constraints of external force. The dynamics of recurrent neural network for realtime force optimization are proposed. For the obtained optimized tip-point force and the motion of legs, we propose the hybrid motion/force control based on adaptive fuzzy system to compensate for the external perturbation and the task-space tracking errors in the environment. The proposed control can confront the uncertainties including approximation task space error and external perturbation. The verification of the proposed control is conducted using the extensive simulations.