Distributed Omniscient Observers for Multi-Agent Systems: Design and Applications
For researchers in multi-agent systems and distributed control, this work provides a novel observer design that relaxes the need for global communication knowledge, enabling applications in game theory and swarm robotics.
This paper proposes distributed omniscient observers for linear multi-agent systems, enabling each agent to estimate the states of all agents using only local information and without requiring global communication graph knowledge. The observers are applied to distributed Nash equilibrium seeking and emulation of animal social behaviors such as sheepdog herding and honeybee navigation.
This paper proposes distributed omniscient observers for both heterogeneous and homogeneous linear multi-agent systems, such that each agent can correctly estimate the states of all agents. The observer design is based on local input-output information available to each agent, and knowledge of the global communication graph among agents is not necessarily required. The proposed observers can contribute to distributed Nash equilibrium seeking in multi-player games and the emergence of self-organized social behaviors in artificial swarms. Simulation results demonstrate that artificial swarms can emulate animal social behaviors, including sheepdog herding and honeybee dance-based navigation.