Localization and self-calibration of a robot for volcano exploration

This work describes an algorithm for the localization and self calibration of a mobile robot. Data from a DGPS and two optical encoders are fused by an extended Kalman filter (EKF) in order to calculate the absolute position of the robot and to estimate the values of the parameters used by the odometry (wheels radii and wheelbase). The presented self calibrating EKF (EKF_SC) has been tested both on a simulator and on the mobile robot "Robovolc": a six independently actuated wheels robot for volcano exploration. The EKF_SC does not need a separate phase for the parameter identification. Moreover the odometry parameters of the Robovolc robot have been identified both with the UMBmark and with the EKF_SC; some comparative tests show an improvement of the estimated trajectories.