We are interested in finding solutions to the multi-robot path-planning problem that have guarantees on completeness, are robust to communication failure, and incorporate varying team size. In this paper we present an algorithm that addresses the complete multi-robot path-planning problem from two different angles. First, dynamic teams are used to minimize computational complexity per robot and maximize communication bandwidth between team-members. Second, each team is formed into a distributed computer that utilizes surplus communication bandwidth to help achieve better solution quality and to speed-up consensus time. The proposed algorithm is evaluated in three real-world experiments that promote dynamic team formation. In the first experiment, a five mobile robot team plans a set of compatible paths through an office environment while communication quality is disrupted using a tin-can Faraday cage. Results show that the distributed framework of the proposed algorithm drastically speeds-up computation, even when packet loss is as high as 97%. In the second and third experiments, four robots are deployed in a network of three building wings connected by a common room. Results of the latter experiments emphasize a need for dynamic team algorithms that can judiciously choose which subset of the original problem a particular dynamic team should solve.
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- Any-Com Multi-robot Path-Planning with Dynamic Teams: Multi-robot Coordination under Communication Constraints
- Springer Berlin Heidelberg