Assistive formation maintenance for human-led multi-robot systems

In ground-based military maneuvers, group formations require flexibility when traversing from one point to the next. For a human-led team of semi-autonomous agents, a certain level of awareness demonstrated by the agents regarding the quality of the formation is preferable. Through the use of a Multi-Robot System (MRS), this work combines leader-follower principles augmented by an assistive formation maintenance (AFM) method to improve formation keeping and demonstrate a formation-in-motion concept. This is achieved using the Robot Mean Task Allocation method (RTMA), a strategy used to allocate formation positions to each unit within a continuously mobile MRS. The end goal is to provide a military application that allows a soldier to efficiently tele-operate a semi-autonomous MRS capable of holding formation amidst a cluttered environment. Baseline simulation is performed in Player/Stage to show the applicability of our developed model and its potential for expansive research.