Robust configuration control of a mobile robot with uncertainties

A configuration control problem of a forklift vehicle considering input disturbances, measurement noises, and modeling errors is investigated. A switching algorithm that controls the vehicle's asymptotical convergence from an initial to a goal configuration and renders robust performance is proposed. A configuration error space representing distance and orientation errors is introduced. The error space is split into three regions: far, near, and orientation-aligned. Using Lyapunov functions, control laws in individual regions are developed, and their asymptotical stability is proven. The robustness of the proposed control laws to uncertainties is analyzed. Its effectiveness is verified through simulation and experiment using an autonomous forklift.