BIND-USBL: Bounding IMU Navigation Drift using USBL in Heterogeneous ASV-AUV Teams

2026-04-13

AI Summary

This study addresses the unbounded cumulative drift inherent in inertial dead reckoning for autonomous underwater vehicles (AUVs) operating in GPS-denied environments by proposing a heterogeneous ASV-AUV cooperative localization framework. The approach leverages a formation of multiple autonomous surface vehicles (ASVs), equipped with ultra-short baseline (USBL) systems, to intermittently correct the AUV’s position estimates. It innovatively links localization performance to survey scale, acoustic coverage, formation geometry, and team composition, and introduces a conflict-graph-based spatially reused TDMA scheduler that enhances message delivery rates and reduces end-to-end latency while avoiding inter-vehicle collisions. Simulation results in HoloOcean demonstrate that the proposed method effectively suppresses AUV localization drift, significantly improving positioning accuracy and system robustness during long-duration missions.

Technology Category

• Intelligent Robots: Localization, Mapping, and Navigation
• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Humans and AI: Planning and Decision Support for Human-Machine Teams

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Location- and context-aware Web and WoT applications and services
• Search and Retrieval-Augmented AI: Vertical and domain-specific search
• Graph Algorithms and Modeling for the Web: Graph embeddings and representation learning for Web-related graphs

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 for shared-channel servicing, and delayed fusion of received USBL updates with drift-prone dead reckoning. The framework is evaluated in the HoloOcean simulator using heterogeneous ASV-AUV teams executing lawnmower coverage missions. The results show that localization performance is shaped by the interaction of survey scale, acoustic coverage, team composition, and ASV-formation geometry. Further, the spatial-reuse scheduler improves per-AUV fix delivery rate without violating the no-collision constraint, while maintaining low end-to-end fix latency.

Problem

• AUV localization
• navigation drift
• GPS-denied environment
• dead-reckoning error
• cooperative localization

Innovation

• cooperative localization
• USBL
• IMU drift bounding
• TDMA scheduling
• heterogeneous ASV-AUV teams