Reward-Free Continual Adaptation for Resilient Space Robots
产业动态
来源：arXiv cs.RO发布时间待核实
arXiv:2608.23452v1 Announce Type: new Abstract: Space robots operate in extreme environments where hardware degradation can critically compromise traditional control strategies. While continual reinforcement learning offers a promising mechanism for online adaptation, it inherently requires access to a reward signal during deployment. However, precise reward computation in space is often infeasible due to the lack of external tracking systems and the overall complexity of the environment.