日本フィジカルAI新聞

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arXiv:2410.06720

Collective perception for tracking people with a robot swarm

Collective perception for tracking people with a robot swarm

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著者: Miquel Kegeleirs, David Garzón Ramos, Guillermo Legarda Herranz, Ilyes Gharbi, Jeanne Szpirer, Olivier Debeir, Ken Hasselmann, Lorenzo Garattoni, Gianpiero Francesca, Mauro Birattari

分類: cs.RO

原文アブストラクト

Swarm perception refers to the ability of a robot swarm to utilize the perception capabilities of each individual robot, forming a collective understanding of the environment. Their distributed nature enables robot swarms to continuously monitor dynamic environments by maintaining a constant presence throughout the space.In this study, we present a preliminary experiment on the collective tracking of people using a robot swarm. The experiment was conducted in simulation across four different office environments, with swarms of varying sizes. The robots were provided with images sampled from a dataset of real-world office environment pictures.We measured the time distribution required for a robot to detect a person changing location and to propagate this information to increasing fractions of the swarm. The results indicate that robot swarms show significant promise in monitoring dynamic environments.