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20202025
most citedModular Deep Reinforcement Learning for Continuous Motion Planning with Temporal Logic

77 citations · 121 across the 8 of their papers we have counts for

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2 papers · 1 filter

cs.FL2020★ 24 cited

Reinforcement Learning Based Temporal Logic Control with Maximum Probabilistic Satisfaction

Mingyu Cai, Shaoping Xiao, Baoluo Li +2

This paper presents a model-free reinforcement learning (RL) algorithm to synthesize a control policy that maximizes the satisfaction probability of linear temporal logic (LTL) spe…

cs.RO2020★ 1 cited

Optimal Probabilistic Motion Planning with Potential Infeasible LTL Constraints

Mingyu Cai, Shaoping Xiao, Zhijun Li +1

This paper studies optimal motion planning subject to motion and environment uncertainties. By modeling the system as a probabilistic labeled Markov decision process (PL-MDP), the…