Abstract
Investigators publish new report on Robotics - Robotics and Automation. According to news reporting originating from Boulder, Colorado, by NewsRx correspondents, research stated, “This letter introduces a sampling-based strategy synthesis algorithm for nondeterministic hybrid systems with complex continuous dynamics under temporal and reachability constraints. We model the evolution of the hybrid system as a two-player game, where the nondeterminism is an adversarial player whose objective is to prevent achieving temporal and reachability goals.” Financial support for this research came from Strategic University Research Partnership. Our news editors obtained a quote from the research from the University of Colorado, “The aim is to synthesize a winning strategy a reactive (robust) strategy that guarantees the satisfaction of the goals under all possible moves of the adversarial player. Our proposed approach involves growing a (search) game-tree in the hybrid space by combining sampling-based motion planning with a novel bandit-based technique to select and improve on partial strategies. We show that the algorithm is probabilistically complete, i.e., the algorithm will asymptotically almost surely find a winning strategy, if one exists.”
NETL
NSTL
IEEE