Temporal logic control in dynamic environments with probabilistic satisfaction guarantees

Mobile robotic systems move in environments that are constantly changing due to the presence of dynamic obstacles. In this work we consider one such environment in which the dynamic nature comes from doors that can open or close during the robot's mission. We derive a solution to the automatic deployment of a robot from a temporal logic specification assuming three different levels of knowledge and sensing capabilities of the robot. Under each one of these settings, the motion of the robot is modeled either as a Markov decision process (MDP) or mixed observability MDP. The objective is to find a control strategy that maximizes the probability of satisfying a specification given in Probabilistic Computation Tree Logic (PCTL). We describe an optimal solution in one setting and sub-optimal, reactive solutions in the other two. We illustrate our methods with simulation results.