ASyMTRe: Automated Synthesis of Multi-Robot Task Solutions through Software Reconfiguration

摘要

This paper describes a methodology for automat ically synthesizing task solutions for heterogeneous multi-robot teams. In contrast to prior approaches that require a manual pre definition of how the robot team will accomplish its task (while perhaps automating who performs which task), our approach automates both the how and the who to generate task solution approaches that were not explicitly defined by the designer a priori. The advantages of this new approach are that it: (1) enables the robot team to synthesize new task solutions that use fundamentally different combinations of robot behaviors for different team compositions, and (2) provides a general mechanism for sharing sensory information across networked robots, so that more capable robots can assist less capable robots in accomplishing their objectives. Our approach, which we call ASyMTRe (Automated Synthesis of Multi-robot Task solutions through software Reconfiguration, pronounced “Asymmetry”), is based on mapping environmental, perceptual, and motor control schemas to the required flow of information through the multi-robot system, automatically reconfiguring the connections of schemas within and across robots to synthesize valid and efficient multi-robot behaviors for accomplishing the team objectives. We validate this approach by presenting the results of applying our methodology to two different teaming scenarios: altruistic cooperation involving multi-robot transportation, and coalescent cooperation involving multi-robot box pushing.