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SC2025顶会

Optimizing Data Acquisitions in Multi-Robot Systems

Yanhao Li, Zijun Xu, Xuanjun Wen, Yanjie Song, Guancheng Li, Shu Yin

2025年份
1被引次数

摘要

We present ROSfs, a novel user-level file system designed to address critical data query inefficiencies in multi-robot systems (MRS). ROSfs introduces an innovative file organization model where robot data is structured as labeled sub-files, coupled with a time-indexed architecture that enables efficient querying of actively modified data. This design enables real-time cross-robot data acquisition and collaboration capabilities previously unattainable in MRS deployments. Our implementation integrates seamlessly with the Robot Operating System (ROS) and has been extensively evaluated using both physical UAV/UGV platforms and data servers. Experimental results demonstrate that ROSfs achieves a 7x reduction in online data query latency under wireless network conditions compared to conventional ROS storage methods, while simultaneously improving data freshness (Age of Information) by up to 271x. These advancements position ROSfs as a transformative solution for high-performance robotic data management in distributed systems.

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