IMU-based localization and slip estimation for skid-steered mobile robots

Localization and wheel slip estimation of a skid- steered mobile robot is challenging because of the complex wheel/ground interactions and kinematics constraints. In this paper, we present a localization and slip estimation scheme for a skid-steered mobile robot using low-cost inertial measurement units (IMU). We first analyze the kinematics of the skid-steered mobile robot and present a nonlinear Kalman filter (KF)- based simultaneous localization and slip estimation scheme. The KF-based localization design incorporates the wheel slip estimation and utilizes robot velocity constraints and estimates to overcome the large drift resulting from the integration of the IMU acceleration measurements. The estimation methodology is tested and validated experimentally with a computer vision- based localization system.