Plasticity in Collective Decision-Making for Robots: Creating Global Reference Frames, Detecting Dynamic Environments, and Preventing Lock-ins

Mohammad Divband Soorati, Maximilian Krome, Marco Mora-Mendoza, Javad Ghofrani, Heiko Hamann

Abstract

Swarm robots operate as autonomous agents and a swarm as a whole gets autonomous by its capability of collective decision-making. Despite intensive research on models of collective decision-making, the implementation in multi-robot systems is still challenging. Here, we advance the state of the art by introducing more plasticity to the decision-making process and by increasing the scenario difficulty. Most studies on large-scale multi-robot decision-making are limited to one instance of an iterated exploration-dissemination phase followed by successful and permanent convergence. We investigate a dynamic environment that requires constant collective monitoring of option qualities. Once a significant change in qualities is detected by the swarm, it has to collectively reconsider its previous decision accordingly. This is only possible by preventing lock-ins, a global consensus state of no return (i.e., a dominant majority of robots prevents the swarm from switching to another, possibly better option). In addition, we introduce a scenario of increased difficulty as the robots must locate themselves to assess the quality of an option. Using local communication, swarm robots propagate hop-count information throughout the swarm to form a global reference frame. We successfully validate our implementation in many swarm robot experiments concerning robustness to disruptions of the reference frame, scalability, and adaptivity to a dynamic environment.

Original languageEnglish
Title of host publication2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Number of pages6
PublisherIEEE
Publication date11.2019
Pages4100-4105
Article number8967777
ISBN (Print)978-1-7281-4005-6, 978-1-7281-4003-2
ISBN (Electronic)978-1-7281-4004-9
DOIs
Publication statusPublished - 11.2019
Event2019 IEEE/RSJ International Conference on Intelligent Robots and Systems - Macau, China
Duration: 03.11.201908.11.2019
Conference number: 157163

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