Abstract

T181 parameter identification is essential to algorithm development for robot control. This paper proposed an identification method of terrain parameter using extended Kalman filter (EKF) algorithm and the least squares (LSQ) optimization. A kinematic model of a tracked robot is established based on the location of instantaneous centers of rotation (ICR). It is used in applications with EKF where both the GPS and a multi-line lidar are employed to obtain the observational state. The comparison between them is conducted to investigate the error of position and velocities of the robot. A dynamic model of the robot is built by soil shear force formula and combined with LSQ to identify terrain parameters. A tracked platform equipped with multi sensors is employed to carry out an experiment under circular maneuver. The result demonstrates that the proposed method is effective and reliable to identify terrain parameters, which could be employed for future path planning and following development for tracked robots.

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