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AIMS Seminar - Friday 13th March 2020

Mission Planning under Uncertainty for Autonomous Robots

For our autonomous robots to be useful they must act to complete missions, i.e. sequences of actions created to achieve goals or service tasks. However, robotic action execution is not deterministic, therefore techniques for mission planning  under uncertainty are required for autonomous systems. In this talk I will motivate the combination of Markov decision processes and probabilistic verification as a framework for robot mission planning under uncertainty. I will motivate this using examples of mobile service robots capable of long-term autonomy in everyday environments. Following this I will present some of our recent work on extending this framework to embed reinforcement learning of actions, human interventions, multiple mission objectives, and multiple robots.