EnCoMP: Enhanced Covert Maneuver Planning using Offline Reinforcement Learning

arXiv:2403.20016v1 Announce Type: cross
Abstract: Cover navigation in complex environments is a critical challenge for autonomous robots, requiring the identification and utilization of environmental cover while maintaining efficient navigation. We propose an enhanced navigation system that enables robots to identify and utilize natural and artificial environmental features as cover, thereby minimizing exposure to potential threats. Our perception pipeline leverages LiDAR data to generate high-fidelity cover maps and potential threat maps, providing a comprehensive understanding of the surrounding environment. We train …

abstract artificial arxiv autonomous autonomous robots challenge cs.lg cs.ro environmental environments features identification identify natural navigation offline planning reinforcement reinforcement learning robots type