Control of Large Swarms via Random Finite Set Theory.
Controlling large swarms of robotic agents has many challenges, including but not limited to, computational complexity due to the number of agents, uncertainty in the functionality of each agent in the swarm, and limited knowledge of information of each agent. This work generalizes the swarm state using Random Finite Set (RFS) theory and solves the control problem using model predictive control. The proposed RFS-based approach naturally handled the aforementioned challenges. This work uses information divergence to define the distance between swarm RFS and a desired distribution. A stochastic optimal control problem is formulated using a modified L2^2 distance. Simulation results are shown for this problem formulation.
Publisher URL: http://arxiv.org/abs/1801.07314