Fuzzy Vector Field Orientation Feedback Control-Based Slip Compensation for Trajectory Tracking Control of a Four Track Wheel Skid-steered Mobile Robot

Abstract

Skid-steered mobile robots have been widely used in exploring unknown environments and in military applications. In this paper, the tuning fuzzy Vector Field Orientation (FVFO) feedback control method is proposed for a four track wheel skid-steered mobile robot (4-TW SSMR) using flexible fuzzy logic control (FLC). The extended Kalman filter is utilized to estimate the positions, velocities and orientation angles, which are used for feedback control signals in the FVFO method, based on the AHRS kinematic motion model and velocity constraints. In addition, in light of the wheel slip and the braking ability of the robot, we propose a new method for estimating online wheel slip parameters based on a discrete Kalman filter to compensate for the velocity constraints. As demonstrated by our experimental results, the advantages of the combination of the proposed FVFO and wheel slip estimation methods overcome the limitations of the others in the trajectory tracking control problem for a 4-TW SSMR.