Natural Deadlock Resolution for Multi-agent Multi-Swarm Navigation

This paper presents a nonlinear and discontinuous control scheme for two-dimensional (2-D) multi-agent multi-swarm navigation that resolves deadlocks, without heuristics, by agents reacting purely to their constrained dynamics. The method is based on extensions of Gauss's Principle of Least Constraint that dynamically identify, incorporate, and stabilize time-varying sets of constraints and that integrate actuator saturation and delay. The deadlocks are naturally resolved by formulating the 2-D leader following and collision avoidance requirements as decomposed inequality constraints along the X and Y axes and by asymmetrically assigning zero collision avoidance constraint value to a specific branch. Numerical results are presented for two agents and two 15-agent swarms resolving nominal deadlocks at a computation time order of 10 microseconds, demonstrating the efficacy and efficiency of the proposed approach.