Intercepting Rogue Robots: An Algorithm for Capturing Multiple Evaders With Multiple Pursuers

We propose a distributed algorithm for the cooperative pursuit of multiple evaders using multiple pursuers in a bounded convex environment. The algorithm is suitable for intercepting rogue drones in protected airspace, among other applications. The pursuers do not know the evaders' policy, but by using a global area-minimization strategy based on a Voronoi tessellation of the environment, we guarantee the capture of all evaders in finite time. We present a decentralized version of this policy applicable in two-dimensional (2-D) and 3-D environments, and show in multiple simulations that it outperforms other decentralized multipursuer heuristics. Experiments with both autonomous and human-controlled robots were conducted to demonstrate the practicality of the approach. Specifically, human-controlled evaders are not able to avoid capture with the algorithm.