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Shaoping Xiao

2 accepted papers

2021

Modular Deep Reinforcement Learning for Continuous Motion Planning With Temporal Logic

RA-L 2021

This letter investigates the motion planning of autonomous dynamical systems modeled by Markov decision processes (MDP) with unknown transition probabilities over continuous state and action spaces. Linear temporal logic (LTL) is used to specify high-level tasks over infinite horizon, which can be c

Cited by 101SourcecodeScholar
2021

Reinforcement Learning Based Temporal Logic Control with Maximum Probabilistic Satisfaction

ICRA 2021poster

This paper presents a model-free reinforcement learning (RL) algorithm to synthesize a control policy that maximizes the satisfaction probability of complex tasks, which are expressed by linear temporal logic (LTL) specifications. Due to the consideration of environment and motion uncertainties, we…

Cited by 42SourcecodeScholar