Intra-robot replanning to enable team plan conditions

Abstract

Individual team members are the building blocks of successful multi-robot teams in dynamic competitive domains. The current approach to designing a team is to divide the planning into a hierarchy by separating team coordination and task assignment - global planning - from task planning and execution - local planning. The global planner must make assumptions based on simplified models of dynamics and/or opponents, and as such certain conditions are assumed true when globally planning but are not always true at local execution time. In this paper, we describe several algorithms for intra-robot replanning that allow the individual robots to enable the conditions of their tasks. We then demonstrate improvements in task completion when the robots are capable of replanning their task(s) and their teammates' task(s) in a simplified robot soccer domain. We further show preliminary results on learning when to replan.