Path Tracking Control of a Mobile Robot by Using Dual Estimation Algorithm

Abstract

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 to overcome the previous limitations. The estimated values such as the robot's positions and wheel slips are obtained based on the Kalman filtering technique. As demonstrated by our experimental results, the advantages of the new method are effective to overcome the slip limitations in the path tracking control problem of a four-track wheel skid-steered mobile robot (4-TW SSMR).