Weixu Zhu, Michael Allwright, Mary Katherine Heinrich, Sinan Oğuz, Anders Lyhne Christensen, and Marco Dorigo (May 2020)
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Formation control in a robot swarm targets the overall swarm shape and relative positions of individual robots during navigation. Existing approaches typically depend on a global reference or a predefined static communication topology. We propose a novel approach without these constraints, by extending the concept of `mergeable nervous systems' to establish distributed asymmetric control via a self-organized wireless communication network. In simulated experiments with UAVs and mobile robots, we demonstrate our approach for four sub-tasks of formation control: formation establishment, maintenance during motion, deformation, and splitting and merging. We also demonstrate usage with time-and-position cooperative and reactive motion planning, and assess the fault tolerance and scalability of our approach.
All the code and data is available on github : https://github.com/freedomcondor/vns2.0/tree/vns1.0_data,
The following video is about 30M, click to download
The video is also available on Google Drive