Decision theoretic task coordination for a visually-guided interactive mobile robot

In this paper, we present a visually-guided mobile robot that is capable of executing a task requiring complex human-robot interaction (HRI). The robot delivers verbal messages among the inhabitants of an office-like environment. Essential to the robot´s robust performance is our behavior-based robot control architecture enhanced with a state of the art decision theoretic planner that takes into account the temporal characteristics of the robot´s actions. The decision theoretic layer is based on the partially observable Markov decision process (POMDP) framework allowing us to achieve principled coordination of complex subtasks implemented as robot behaviors/skills. We compute approximate POMDP policies using the randomized point-based value iteration algorithm and we present heuristics for improving its computational efficiency.