Network Localization Based Planning for Autonomous Underwater Vehicles with Inter-Vehicle Ranging

TL;DR

This paper develops a rigidity-based planning framework for autonomous underwater vehicle swarms that ensures reliable localization through inter-vehicle ranging, accounting for sensor noise and limited sensing range.

Contribution

It introduces tools for analyzing, planning, and controlling multi-AUV networks to maintain network rigidity and improve localization accuracy in challenging environments.

Findings

Successfully generates feasible paths maintaining network rigidity

Guarantees minimum network rigidity throughout the mission

Demonstrates effectiveness in simulated environments

Abstract

Localization between a swarm of AUVs can be entirely estimated through the use of range measurements between neighboring AUVs via a class of techniques commonly referred to as sensor network localization. However, the localization quality depends on network topology, with degenerate topologies, referred to as low-rigidity configurations, leading to ambiguous or highly uncertain localization results. This paper presents tools for rigidity-based analysis, planning, and control of a multi-AUV network which account for sensor noise and limited sensing range. We evaluate our long-term planning framework in several two-dimensional simulated environments and show we are able to generate paths in feasible time and guarantee a minimum network rigidity over the full course of the paths.