Autonomous navigation for planetary exploration by a mobile robot

Abstract

This paper describes a complete approach for localization and path selection of any vehicle like a mobile robot to achieve any planetary exploration missions. In this study, localization process was realized on a mobile robot, Nomad 200, using its odometry and gyro measurements. These sensors information was integrated, by extended Kalman Filter (EKF) algorithm. On the other hand, on a given planetary surface, which can be obtained by using many separated cameras or using backpropagated beacons, a lot of safely traveled paths are formed due to the vehicle mission. A path selection was constructed due to its cost function among the selected paths. In this part, vehicle is forced to select a proper path to reach its target. This selection is performed using cost function of these paths. Cost values are strictly bounded to the surface of the planet. Only simulation results of this section were given. We believe that this path selection study presented here will satisfy valuable results on a real robotic vehicle that is suitable to navigate a planet like a rover.