Efficient and Adaptive Autonomous Guidance and Control of Planetary Rover With Improved Traction Controller and Dynamic Cost Map

ABSTRACT Planetary exploration is rapidly gaining importance within the space research community. Autonomous locomotion of rovers requires consideration of several mobility aspects to ensure safety, including avoiding hazardous areas that can cause the robot to become immobilized in soft soil or damaged in sharp terrains. Furthermore, when executing autonomous guidance, selecting an appropriate path to follow is crucial to reduce energy consumption and improve the overall distance traveled by the rover. This directly impacts the rover's performance and the possible scientific outcome of the mission. This paper addresses the optimization of the autonomous locomotion of Mars rovers by acting on the guidance and control layers. Firstly, an enhanced velocity‐based traction controller is proposed to simultaneously address slip and kinematic incompatibilities while permitting omnidirectional motion. The controller acts directly at the wheel command level to improve traction and tracking performances, reducing position and heading errors. This is achieved by enriching the controller's input with the rover's linear and angular velocity error. The performance metrics evaluated within the traction controller are then used to dynamically update the cost map of the environment. Finally, a higher‐level path planner is integrated, considering kino‐dynamic constraints, continuously providing new trajectories according to the map updates to select high‐traction paths. The proposed framework has been validated through simulation and real‐world experiments on the MaRTA rover of ESA's Planetary Robotics Laboratory. The results demonstrate that the proposed approach achieves better tracking performance and up to 62% traction improvements thanks to the enhanced controller and dynamic cost map updates.