Range-only Collaborative Localization for Ground Vehicles

TL;DR

This paper presents a range-only collaborative localization system for ground vehicles that uses inter-vehicle ranging and communication to achieve high-accuracy real-time absolute pose estimation, validated through simulations and real-world experiments.

Contribution

The paper introduces a novel range-only collaborative localization method with observability analysis and a system design that categorizes vehicles into static and dynamic groups for improved accuracy.

Findings

Simulation results confirm the observability analysis.

Collaborative localization improves accuracy over individual methods.

Real-world experiments demonstrate real-time, high-precision pose estimation.

Abstract

High-accuracy absolute localization for a team of vehicles is essential when accomplishing various kinds of tasks. As a promising approach, collaborative localization fuses the individual motion measurements and the inter-vehicle measurements to collaboratively estimate the states. In this paper, we focus on the range-only collaborative localization, which specifies the inter-vehicle measurements as inter-vehicle ranging measurements. We first investigate the observability properties of the system and derive that to achieve bounded localization errors, two vehicles are required to remain static like external infrastructures. Under the guide of the observability analysis, we then propose our range-only collaborative localization system which categorize the ground vehicles into two static vehicles and dynamic vehicles. The vehicles are connected utilizing a UWB network that is capable of both producing inter-vehicle ranging measurements and communication. Simulation results validate the observability analysis and demonstrate that collaborative localization is capable of achieving higher accuracy when utilizing the inter-vehicle measurements. Extensive experimental results are performed for a team of 3 and 5 vehicles. The real-world results illustrate that our proposed system enables accurate and real-time estimation of all vehicles' absolute poses.