Mission-based autonomy core for decentralized mobile UGV swarms

Planning of missions by fully decentralized and autonomous robot swarms in dynamically changing disaster areas is a tough challenge. Therefore, this paper provides a novel real time autonomy core for unmanned ground vehicles (UGVs) that generates usable, but not necessarily optimal trajectories based on specific missions. These are defined implicitly, without assigning goal states to single agents, by direct potential functions which may include nonlinearities, unsteadiness, and discrete parts for specifying complex behavior which is achieved without state machines or behavior trees. In addition, the autonomy core is designed to exchange small data packages between agents via unreliable mesh networks based on UDP or LongRange (LoRa) or a physically simulated mesh network inside the simulation.The availability of information from other agents improves the behavior of the swarm but is not required to fulfill a mission. Interfaces to common robotic middleware are provided to integrate simulations and real agents.