人と接するロボットのための並列タスク設計への最適化によるアプローチ

抄録

Robots that interact with humans in household environments are required to achieve multiple simultaneous tasks such as carrying objects, collision avoidance and conversation with human, in real time. This paper presents a design framework of multiple human-interacting tasks to meet the requirement by considering stochastic behavior of humans. The proposed designing method first introduces petri-net for parallel multiple tasks. The petri-net formulation is converted to Markov decision processes and processed in optimal control framework. Multiple task arbitration is resolved by optimization with approximated value functions. Two tasks of safety confirmation and conversation tasks are mutually interacting and expressed by petri-net. Tasks that normally tend to be designed by integrating many if-then rules can be dealt with in a systematic manner in the proposed framework, that is, in a state estimation and optimization framework. The proposed arbitration method was verified by simulations and experiments using RI-MAN, which was developed to do interactive tasks with humans.