Adaptive selection of reactive/deliberate planning for the dynamic environment

Abstract

This paper proposes and evaluates a methodology for multi-agent real-time reactive planning. In addition to the feature of conventional real-time reactive planning, which can react in a dynamic environment, our planning can perform deliberate planning when, for example, the robot has enough time to plan its next action. The proposed planning features three kinds of agents: a behavior agent that controls simple behavior, a planning agent that makes plans to achieve its goals, and a behavior selection agent that intermediates between behavior agents and planning agents. They coordinate a plan in an emergent way for the planning system as a whole. We confirmed the effectiveness of our planning by means of a simulation. Furthermore, we implemented an active vision system, which is the first stage of building the real-world agent, and used it to verify the real-world effectiveness of our planning.