HydraCollab: Adaptive Collaborative-Perception for Distributed Autonomous Systems

• URL: http://arxiv.org/abs/2607.00191v1
• Date: Tue, 30 Jun 2026 21:16:43 GMT
• Title: HydraCollab: Adaptive Collaborative-Perception for Distributed Autonomous Systems
• Abstract summary: Collaborative-perception enables multi-robot systems to enhance situational awareness by sharing perceptual information.<n>Existing collaborative-perception systems face an inherent trade-off between communication bandwidth requirements and perception accuracy.<n>We propose HydraCollab, an adaptive collaborative-perception framework that minimizes communication overhead without sacrificing perception performance.
• Score: 8.659332706616214
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• 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. Extensive evaluations on the V2X-R, V2X-Radar and UAV3D-mini datasets demonstrate that HydraCollab achieves the best overall trade-off between accuracy and communication cost among existing collaborative-perception methods. Relative to SOTA Where2comm, HydraCollab uses only 41% of the bandwidth on V2X-R and 26% on V2X-Radar while improving performance by 0.78% and 0.75% respectively. Our code and models are available at https://github.com/AICPS/HydraCollab.

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