Abstract-This paper describes an approach to the modeling and control of multiagent populations composed of a large number of agents. The complexity of population modeling is avoided by assuming a stochastic approach, under which the agent distribution over the state space is modeled. The dynamics of the state probability density functions is determined, and a control problem of maximizing the probability of robotic presence in a given region is introduced. The Minimum Principle for the optimal control of partial differential equations is exploited to solve this problem, and it is applied to the mission control of a simulated large robotic population.
In REF , optimal control is applied to a spatial population model for the specific problem of maximizing swarm presence in a desired location.
Modeling and Optimal Centralized Control of a Large-Size Robotic Population
IEEE Transactions on Robotics
IEEE Transactions on Robotics
Mathematics Computer Science