BIND-USBL: Bounding IMU Navigation Drift using USBL in Heterogeneous ASV-AUV Teams
Pranav Kedia, Rajini Makam, Heiko Hamann, and Suresh Sundaram

TL;DR
BIND-USBL is a cooperative underwater localization framework that uses surface vessels with USBL systems to bound AUV navigation drift in GPS-denied environments, optimizing fix delivery and formation geometry.
Contribution
This work introduces a novel multi-ASV formation and scheduling approach to improve intermittent USBL-based localization for AUVs, addressing geometric and coverage challenges.
Findings
Localization performance depends on survey scale, acoustic coverage, and team geometry.
The proposed scheduler increases fix delivery rate while maintaining low latency.
Simulation results demonstrate improved localization accuracy in heterogeneous ASV-AUV teams.
Abstract
Accurate and continuous localization of Autonomous Underwater Vehicles (AUVs) in GPS-denied environments is a persistent challenge in marine robotics. In the absence of external position fixes, AUVs rely on inertial dead-reckoning, which accumulates unbounded drift due to sensor bias and noise. This paper presents BIND-USBL, a cooperative localization framework in which a fleet of Autonomous Surface Vessels (ASVs) equipped with Ultra-Short Baseline (USBL) acoustic positioning systems provides intermittent fixes to bound AUV dead-reckoning error. The key insight is that long-duration navigation failure is driven not by the accuracy of individual USBL measurements, but by the temporal sparsity and geometric availability of those fixes. BIND-USBL combines a multi-ASV formation model linking survey scale and anchor placement to acoustic coverage, a conflict-graph-based TDMA uplink scheduler…
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