SENSOR NETWORK-MEDIATED MULTI-ROBOT TASK ALLOCATION

We address the Online Multi-Robot Task Allocation (OMRTA) problem. Our approach relies on a computational and sensing fabric of networked sensors embedded into the environment. This sensor network acts as a distributed sensor and computational platform which computes a solution to OMRTA and directs robots to the vicinity of tasks. We term this Distributed In-Network Task Allocation (DINTA). We describe DINTA, and show its application to multi-robot task allocation in simulation, laboratory, and field settings. We establish that such network-mediated task allocation scales well, and is especially amendable to simple, heterogeneous robots.