Nonlinear Kalman filter-based trajectory error analysis of skid-steered mobile robots

Abstract

Skid-steered mobile robots have been widely used for terrain navigation and exploration. The absence of a steering system makes the robot mechanically robust and simple.Due to the varying tire/ground interactions and complex dynamics/kinematics models, it is challenging localization and tracking control for such mobile robots. In this paper, we present a localization and slip estimation scheme for a skid-steered mobile robot using low-cost inertial measurement units, We first analyze the kinematics of the skid-steered mobile robot, secondly we establish an Gauss-Markov error model, then we present a nonlinear Kalman filter based simultaneous localization and slip estimation scheme. The estimation methodology is tested and validated experimentally with a computer vision-based localization system.