Scalable and Low Power Localization for Underwater Robots
Author(s)
Afzal, Sayed Saad; Rademacher, Jack; Chen, Weitung; Wang, Purui; Adib, Fadel
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Localization is a critical task for underwater robots, yet today’s underwater localization systems are limited by their accuracy, scalability, and/or energy consumption (i.e., longevity).
We present the design, implementation, and evaluation of
EchoBLUE– an accurate, scalable, and low-power localization system for underwater robots.
In EchoBLUE, an underwater robot transmits SONARstyle (FMCW) signals, and leverages ultra-low power underwater backscatter nodes as location anchors. EchoBLUE’s
design introduces two key innovations. The first is a novel
doppler compensation mechanism that enables it to accurately self-localize under mobility: the technique employs a
cross-chirp mechanism that exploits the quad-band nature of
the resulting backscatter response to overcome the rangedoppler ambiguity. Second, it introduces the first semi-active
retrodirective underwater backscatter design and uses it for
location anchors; this design achieves wide bandwidth to
backscatter the full FMCW signal, enabling fine-grained localization.
We implemented a proof of concept prototype of EchoBLUE
by building a base station mounted on a BlueROV2 underwater robot and custom-designed low-power retrodirective
location anchors deployed in a pool. Our evaluation across
700 real-world trials demonstrates that EchoBLUE achieves a
median 3D localization accuracy of 28 cm and 90th percentile
of 48 cm. Moreover, these anchors consume only 740 𝜇𝑊 for
semi-active backscatter, paving the way for truly low-power
and scalable underwater localization.
Date issued
2025-11-21Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science; Program in Media Arts and Sciences (Massachusetts Institute of Technology)Publisher
ACM|The 31st Annual International Conference on Mobile Computing and Networking
Citation
Sayed Saad Afzal, Jack Rademacher, Weitung Chen, Purui Wang, and Fadel Adib. 2025. Scalable and Low Power Localization for Underwater Robots. In Proceedings of the 31st Annual International Conference on Mobile Computing and Networking (ACM MOBICOM '25). Association for Computing Machinery, New York, NY, USA, 1075–1090.
Version: Final published version
ISBN
979-8-4007-1129-9