Market-based Multirobot Coordination Using Task Abstraction

Abstract

In this paper, we introduce a novel approach to multirobot coordination that works by simultaneously distributing task allocation, mission planning, and execution among members of a robot team. By combining traditional hierarchical task decomposition techniques with recent developments in market-based multirobot control, we obtain an efficient and robust distributed system capable of solving complex problems. Essentially, we have extended the TraderBots market-based architecture to include a mechanism that distributes tasks among robots at multiple levels of abstractions, represented as task trees. Results are presented for a simulated area reconnaissance scenario.