Integration of Probability Collectives for Collision Avoidance in AGENTFLY

Rising deployment of Unmanned Aerial Assets in complex operations requires innovative automatic coordination algorithms, especially for decentralized collision avoidance. The paper investigates a stochastic Probability Collectives (PC) optimizer for the collision avoidance problem defined as an optimization task where efficiency criteria, collision penalties and airplanes’ missions are integrated in an objective function. The paper provides two different implementation approaches of the proposed method – complex multiagent deployment distributes the PC optimization process among airplanes and the Process Integrated Mechanism approach replaces communication with optimizer migration. Both implementations have been developed and tested on an airspace multi-agent framework AGENTFLY.