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CADENCE and DADENCE Extended to Dynamic Coverage Scenarios

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Hugo Gandhi and other authors extended CADENCE and its decentralized version DADENCE—two multi-agent communication network coverage algorithms—to a dynamic version of POCGAGP (DPOCGAGP), adding two deployment-time perturbation settings, Agent Loss and World Change, for multi-agent establishment of a fully covering communication network in unknown constrained spaces. The authors state that on more than 4,500 benchmark test cases of different scales and structures, the improved algorithms outperform another state-of-the-art baseline algorithm. This work is currently limited to simulation benchmark evaluation and has not yet involved real-machine validation.

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  1. Adaptive Coverage Algorithms for Mobile Ad Hoc Networks in Dynamic Worlds: CADENCE and DADENCE Extended to DPOCGAGP

    The study extends two algorithms, CADENCE and its decentralized version DADENCE, to the dynamic version of POCGAGP (DPOCGAGP), adding two deployment-time perturbation settings, Agent Loss and World Change, for multi-agent systems to establish a fully covering communication network in unknown constrained spaces. On more than 4,500 benchmark test cases of varying scale and structure, the improved algorithms outperform another state-of-the-art benchmark algorithm. The work focuses on simulation benchmark evaluation and has not yet involved real-robot validation.

    arXiv cs.RO ·

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Planning and decision makingRobot models and learningResearch papers

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