Safe Learning for Uncertainty-Aware Planning via Interval MDP Abstraction
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Control Systems Letters"
DOI: 10.1109/lcsys.2022.3173993
Abstract: We study the problem of refining satisfiability bounds for partially-known stochastic systems against planning specifications defined using syntactically co-safe Linear Temporal Logic (scLTL). We propose an abstraction-based approach that iteratively generates high-confidence Interval Markov Decision… read more here.
Keywords: learning uncertainty; planning via; uncertainty aware; aware planning ... See more keywords
A path planning approach for mobile robots using short and safe Q-learning
Sign Up to like & getrecommendations! Published in 2022 at "PLoS ONE"
DOI: 10.1371/journal.pone.0275100
Abstract: Path planning is a major challenging problem for mobile robots, as the robot is required to reach the target position from the starting position while simultaneously avoiding conflicts with obstacles. This paper refers to a… read more here.
Keywords: mobile robots; path; safe learning; path planning ... See more keywords