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| Autores principales: | , , , , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2410.06720 |
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| _version_ | 1866910641934041088 |
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| author | Kegeleirs, Miquel Ramos, David Garzón Herranz, Guillermo Legarda Gharbi, Ilyes Szpirer, Jeanne Debeir, Olivier Hasselmann, Ken Garattoni, Lorenzo Francesca, Gianpiero Birattari, Mauro |
| author_facet | Kegeleirs, Miquel Ramos, David Garzón Herranz, Guillermo Legarda Gharbi, Ilyes Szpirer, Jeanne Debeir, Olivier Hasselmann, Ken Garattoni, Lorenzo Francesca, Gianpiero Birattari, Mauro |
| contents | 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2410_06720 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Collective perception for tracking people with a robot swarm Kegeleirs, Miquel Ramos, David Garzón Herranz, Guillermo Legarda Gharbi, Ilyes Szpirer, Jeanne Debeir, Olivier Hasselmann, Ken Garattoni, Lorenzo Francesca, Gianpiero Birattari, Mauro Robotics 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. |
| title | Collective perception for tracking people with a robot swarm |
| topic | Robotics |
| url | https://arxiv.org/abs/2410.06720 |