Complex Task Allocation For Multiple Robots

Abstract

Recent research trends and technology developments are bringing us closer to the realization of autonomous multirobot systems performing increasingly complex missions. However, existing multirobot task allocation mechanisms treat tasks as simple, indivisible entities and ignore any inherent structure and semantics that such complex tasks might have. These properties can be exploited to produce more efficient team plans by giving individual robots the ability to come up with new ways to perform a task, or by allowing multiple robots to cooperate by sharing the subcomponents of a task, or both. In this paper, we introduce the complex task allocation problem and describe a distributed solution for efficiently allocating a set of complex tasks to a robot team. The advantages of explicitly modeling complex tasks during the allocation process is demonstrated by a comparison of our approach with existing task allocation algorithms in an area reconnaissance scenario. An implementation on a team of outdoor robots further validates our approach.