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Published on: October 17, 2025
Cooperative optimal control: broadening the reach of bio-inspiration
Cheng Shao1, Dimitrios Hristu-Varsakelis
1Department of Mechanical Engineering, University of Maryland, College Park, MD 20742, USA. cshao@umd.edu
Abstract:
Inspired by the process by which ants gradually optimize their foraging trails, this paper investigates the cooperative solution of a class of free final time, partially constrained final state optimal control problems by a group of dynamical systems. We propose an iterative, pursuit-based algorithm which generalizes previously proposed models and converges to an optimal solution by iteratively optimizing an initial feasible trajectory/control pair. The proposed algorithm requires only short-range, limited interactions between group members, avoids the need for a 'global map' of the environment in which the group evolves, and solves an optimal control problem in 'small' pieces, in a manner which will be made precise. The performance of the algorithm is illustrated in a series of simulations and laboratory experiments.
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