Autonomous navigation of a rover on Mars surface can improve very significantly the daily traverse, particularly when driving away from the lander, into unknown areas. The autonomous navigation process developed at CNES is based on stereo cameras perception, used to build a model of the environment and generate trajectories. Multiple perception merging with propagation of the locomotion and localization errors have been implemented. The algorithms developed for Mars exploration programs, the vision hardware, the validation tools, experimental platforms and results of evaluation are presented. Portability and the evaluation of computing resources for implementation on a Mars rover are also addressed. The results show that the implementation of autonomy requires only a very small amount of energy and computing time and that the rover capabilities are fully used, allowing a much longer daily traverse than what is enabled by purely ground-planned strategies.
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