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, permitting omnidirectional motion while
simultaneously addressing slip and kinematic incompatibilities. The
controller acts directly at the wheel command level to further improve
traction and tracking performances, reducing position and heading
errors. 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 paths
according to the map updates. The proposed framework has been validated
through simulation and real-world experiments on the MaRTA rover of
ESA’s Planetary Robotics Laboratory. The results demonstrated that the
proposed controller achieves better traction and tracking performance,
further improved by the dynamic cost map updates.
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