Dual Estimation for the Path Tracking Control of a Four Track Wheel Skid-Steered Mobile Robot

Skid-steered mobile robots have been developed to explore unknown environments, especially in rough terrain situations, where the wheel slips always occur and vary when the robot is traveling with different trajectory shapes. The wheel slippage limits the traction and braking abilities of the robot. In this paper, we propose a new dual estimation algorithm for the robot’s position and wheel slip estimations based on the Kalman filtering technique. As demonstrated by our experimental results, the advantages of the new method overcome the limitations of the others in the path tracking control problem of a four track wheel skidsteered mobile robot (4-TW SSMR).