详细信息
- 来源站点
- ArXiv CS.CV
- 作者
- Luke Chen, Cheng-Ju Wu, David R. Martin, Qilin Ye, Pramod Khargonekar, Mohammad Abdullah Al Faruque
- 文章类型
- PAPER
- 语言
- en
- 发布日期
- 2026-07-02
摘要
arXiv:2607.00191v1 Announce Type: cross Abstract: Collaborative-perception enables multi-robot systems to enhance situational awareness by sharing perceptual information. Existing collaborative-perception systems face an inherent trade-off between communication bandwidth requirements and perception accuracy, where methods that exchange more information achieve better perception results at the cost of increased communication overhead. However, real-world communication networks impose bandwidth constraints that require minimizing communication overhead without sacrificing perception performance. To address this challenge, we propose HydraCollab, an adaptive collaborative-perception framework that (i) selectively transmits the most informative sensor features and (ii) dynamically employs collaboration strategies (intermediate or late) based on spatial confidence maps.
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