ROSYJun 4, 2020

Distributed Localization without Direct Communication Inspired by Statistical Mechanics

arXiv:2006.02658v11 citations
Originality Incremental advance
AI Analysis

This addresses the problem of enabling large-scale, anonymous robotic swarms to localize efficiently for tasks like shape formation, though it is an incremental improvement over existing distributed methods.

The paper tackles distributed localization for robotic swarms by introducing a virtual particle exchange algorithm that enables robots to determine their relative positions using only sensor readings, without direct communication or fixed beacons, achieving scalability and accuracy in simulations with up to 10,000 robots and experiments with 52 robots.

Distributed localization is essential in many robotic collective tasks such as shape formation and self-assembly.Inspired by the statistical mechanics of energy transition, this paper presents a fully distributed localization algorithm named as virtual particle exchange (VPE) localization algorithm, where each robot repetitively exchanges virtual particles (VPs) with neighbors and eventually obtains its relative position from the virtual particle (VP) amount it owns. Using custom-designed hardware and protocol, VPE localization algorithm allows robots to achieve localization using sensor readings only, avoiding direct communication with neighbors and keeping anonymity. Moreover, VPE localization algorithm determines the swarm center automatically, thereby eliminating the requirement of fixed beacons to embody the origin of coordinates. Theoretical analysis proves that the VPE localization algorithm can always converge to the same result regardless of initial state and has low asymptotic time and memory complexity. Extensive localization simulations with up to 10000 robots and experiments with 52 lowcost robots are carried out, which verify that VPE localization algorithm is scalable, accurate and robust to sensor noises. Based on the VPE localization algorithm, shape formations are further achieved in both simulations and experiments with 52 robots, illustrating that the algorithm can be directly applied to support swarm collaborative tasks.

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