Efficient distributed multi-robot localization: A target tracking inspired design

Abstract

The main reported solutions for the problem of multi-robot relative localization require synchronous communication between robots, where the network should communicate each time a relative measurement is logged in the team. This paper proposes a localization method, which can accommodate communication at a low predefined rate rather than forcing communication each time a measurement is logged. This is achieved without explicitly accumulating past measurements locally at each robot. This capability is necessary to support increasing number of robots in a team, under finite communication and computation resources. The design includes a novel fusion strategy, a consistent estimation method, and a state based initialization method, embedded in a distributed target tracking framework. The design is efficient in terms of computation demand, since it scales linearly with the number of robots. Additionally, the design is efficient in terms of communication demand, since communication is neither required to be synchronized with sensor readings, nor constrained to a specific network topology. The paper validates the proposed approach for its initialization capability, consistency of estimates, and robustness of performance, through several numerical simulations and using a publicly available multi-robot data set.