Beyond Reynolds: A Constraint-Driven Approach to Cluster Flocking
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In this paper, we present an original set of flocking rules using the ecologically-inspired paradigm for control of multi-robot systems. We translate these rules into a constraint-driven optimal control problem where the agents minimize energy consumption subject to safety and task constraints. We prove several properties about the feasible space of the optimal control problem and show that velocity consensus is an optimal solution. We also motivate the inclusion of slack variables in constraint-driven problems when the global state is only partially observable by each agent. Finally, we present a locally-optimal solution that can be implemented in real time and provide a set of sufficient conditions to guarantee velocity consensus. We validate this control algorithm in simulation.
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