Decentralized Localization in Homogeneous Swarms Considering Real-World Non-Idealities

This letter presents a decentralized algorithm that allows a swarm of identically programmed agents to cooperatively estimate their global poses using local range and bearing measurements. The design of our algorithm explicitly considers the phase asynchrony of each agent's local clock, moreover, the execution of our algorithm does not require each agent to actively keep the same neighbors over time. A theoretical analysis about the effect of each agent's sensing noise and communication loss is given, in addition, we validate the presented algorithm via experiments running on a swarm of up to 256 simulated robots and a swarm of 100 physical robots. The results from the experiments show that the presented algorithm allows each agent to estimate its global pose quickly and reliably. Video of 100 robots executing the presented algorithm as well as supplementary material can be found in [1] and [2].