In this paper, we propose a distributed version of the Hungarian method to solve the well-known assignment problem. In the context of multirobot applications, all robots cooperatively compute a common assignment that optimizes a given global criterion (e.g., the total distance traveled) within a finite set of local computations and communications over a peer-to-peer network. As a motivating application, we consider a class of multirobot routing problems with "spatiotemporal" constraints, i.e., spatial targets that require servicing at particular time instants. As a means of demonstrating the theory developed in this paper, the robots cooperatively find online suboptimal routes by applying an iterative version of the proposed algorithm in a distributed and dynamic setting. As a concrete experimental test bed, we provide an interactive "multirobot orchestral" framework, in which a team of robots cooperatively plays a piece of music on a so-called orchestral floor. Index Terms-Distributed algrithms, multi-robot systems, optimal matching, task allocation.
Chopra et al. propose a distributed version of Hungarian method for solving the task assignment problems, and prove that all robots converge to a common optimal assignment under a synchronous implementation REF .
A Distributed Version of the Hungarian Method for Multirobot Assignment
IEEE Transactions on Robotics
IEEE Transactions on Robotics
Computer Science Mathematics