End-to-End Vision-Language-Action Policies for Autonomous Lunar Rover Docking
End-to-End Vision-Language-Action Policies for Autonomous Lunar Rover Docking
This study introduces a vision-language-action policy for autonomous lunar rover docking, designed to handle extreme lunar conditions. The policy is trained in a high-fidelity simulation environment and adapts its execution horizon to balance safety and computational efficiency, showing competitive performance compared to modular navigation systems under unseen perceptual disturbances.
Source: arXiv Robotics — research abstracts · Read original article ↗
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data. However, their applicability and performance have yet to be characterized for lunar surface operations. In this study, we design a vision-language-action policy for autonomous lunar rover docking and characterize its performance relative to a modular navigation pipeline. We develop a scalable training framework that generates safety-aware expert demonstrations in a high-fidelity lunar simulation environment. In
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Source：arXiv Robotics — research abstracts · arxiv.org