Belief Aided Navigation using Bayesian Reinforcement Learning for Avoiding Humans in Blind Spots

arXiv:2403.10105v1 Announce Type: cross
Abstract: Recent research on mobile robot navigation has focused on socially aware navigation in crowded environments. However, existing methods do not adequately account for human robot interactions and demand accurate location information from omnidirectional sensors, rendering them unsuitable for practical applications. In response to this need, this study introduces a novel algorithm, BNBRL+, predicated on the partially observable Markov decision process framework to assess risks in unobservable areas and formulate movement strategies under uncertainty. BNBRL+ consolidates …

abstract applications arxiv bayesian belief blind cs.ai cs.lg cs.ro demand environments however human humans information interactions location mobile navigation practical reinforcement reinforcement learning rendering research robot robot navigation sensors them type