AUV Swarm Self-Localization via Acoustic Timing
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Solution Overview
Problem
Current autonomous vehicle systems face challenges in localizing individual units within a swarm, especially in turbid or navigationally challenging environments, requiring additional resources and increasing the size, weight, and cost of the system, while also potentially compromising detection security.
Innovation Solution
A self-localizing vehicle swarm method that uses acoustic communications signals to determine the distance between nodes and calculate their positions, allowing for accurate localization of all members with minimal impact on system size, weight, power, and cost, and only requiring a single node at a known location.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If additional surface vehicles and towed sonar arrays are deployed to track and localize AUVs in the swarm, then localization accuracy is improved, but system size, weight, power, and cost increase
Solution Approach 1:
Each AUV in the swarm autonomously performs localization functions by transmitting acoustic signals and processing timing data from other nodes. The system serves itself through distributed peer-to-peer measurement rather than requiring external localization infrastructure, eliminating the need for additional surface vehicles and towed arrays.
Solution Approach 2:
The centralized localization function is segmented and distributed across all individual AUV nodes in the swarm. Each node independently performs signal transmission, timing measurement, and position calculation, transforming a single-point localization system into a distributed network where every node contributes to and benefits from the localization capability.
2Measurement precision
If additional towed sonar arrays are deployed to track larger swarms, then localization coverage is improved, but navigation speed is reduced
Solution Approach 1:
The localization system dynamically adapts to varying swarm sizes and configurations without requiring physical reconfiguration. As nodes join or leave the swarm, the acoustic network automatically recalibrates through continuous bidirectional timing measurements, maintaining full localization coverage across dynamic swarm compositions without slowing navigation.
3Measurement precision
If towed sonar arrays are used for localization, then tracking capability is improved, but detection security is compromised
Solution Approach 1:
The external localization infrastructure (towed sonar arrays and surface vehicles) is extracted from the system and replaced with intrinsic onboard acoustic transmitters and receivers on each AUV. This eliminates the physical trail left by towed arrays while maintaining full tracking capability through the distributed acoustic network.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enables accurate localization of each node within the swarm in real-time, reducing the need for additional hardware and maintaining system efficiency, while avoiding detection in sensitive operations.
Implementation Method 1
measuring the distance between each node of the at least four nodes and each of the other nodes of the at least four nodes via the timing of an acoustic communication signal sent between each node and each of the other nodes
Data Source
AI summary
A self-localizing autonomous underwater vehicle swarm that is operable to accurately localize each individual unit within the swarm while only requiring a single node at a known location to do so. The methods described herein can localize all members of a swarm with minimal, if any, effect on the size, weight, power, and cost of a system.