Lifelong adaptation in heterogeneous multi-robot teams: Response to continual variation in individual robot performance

Generating teams of robots that are able to perform their tasks over long p eriods of time requires the robots to be responsive to continual changes in robot team member capabilities and to changes in the state of the environm ent and mission. In this article, we describe the L-ALLIANCE architecture, which enables teams of heterogeneous robots to dynamically adapt their acti ons over time. This architecture, which is an extension of our earlier work on ALLIANCE, is a distributed, behavior-based architecture aimed for use i n applications consisting of a collection of independent tasks. The key iss ue addressed in L-ALLIANCE is the determination of which tasks robots shoul d select to perform during their mission, even when multiple robots with he terogeneous, continually changing capabilities are present on the team. In this approach, robots monitor the performance of their teammates performing common tasks, and evaluate their performance based upon the time of task c ompletion. Robots then use this information throughout the lifetime of thei r mission to automatically update their control parameters. After describin g the L-ALLIANCE architecture, we discuss the results of implementing this approach on a physical team of heterogeneous robots performing proof-of-con cept box pushing experiments. The results illustrate the ability of L-ALLIA NCE to enable lifelong adaptation of heterogeneous robot teams to continuin g changes in the robot team member capabilities and in the environment.