TY - JOUR AU - Lacerda, Bruno AU - Parker, David AU - Hawes, Nick PY - 2017/06/05 Y2 - 2024/03/28 TI - Multi-Objective Policy Generation for Mobile Robots under Probabilistic Time-Bounded Guarantees JF - Proceedings of the International Conference on Automated Planning and Scheduling JA - ICAPS VL - 27 IS - 1 SE - Robotics Track DO - 10.1609/icaps.v27i1.13865 UR - https://ojs.aaai.org/index.php/ICAPS/article/view/13865 SP - 504-512 AB - <p> We present a methodology for the generation of mobile robot controllers which offer probabilistic time-bounded guarantees on successful task completion, whilst also trying to satisfy soft goals. The approach is based on a stochastic model of the robot’s environment and action execution times, a set of soft goals, and a formal task specification in co-safe linear temporal logic, which are analysed using multi-objective model checking techniques for Markov decision processes. For efficiency, we propose a novel two-step approach. First, we explore policies on the Pareto front for minimising expected task execution time whilst optimising the achievement of soft goals. Then, we use this to prune a model with more detailed timing information, yielding a time-dependent policy for which more fine-grained probabilistic guarantees can be provided. We illustrate and evaluate the generation of policies on a delivery task in a care home scenario, where the robot also tries to engage in entertainment activities with the patients. </p> ER -