Large-Scale UWB Anchor Calibration and One-Shot Localization Using Gaussian Process

TL;DR

This paper introduces a Gaussian Process-based framework for large-scale UWB anchor calibration and one-shot localization, combining UWB and LiDAR data to improve accuracy and efficiency in obstructed, expansive environments.

Contribution

It presents a novel fusion-based calibration and localization method that achieves accurate anchor estimation with a single sampling in large areas, addressing challenges of traditional methods.

Findings

Achieves accurate anchor calibration with one sampling in 600x450 m areas

Reduces search range for loop closure, improving localization speed and accuracy

Enhances localization reliability in obstructed, large-scale environments

Abstract

Ultra-wideband (UWB) is gaining popularity with devices like AirTags for precise home item localization but faces significant challenges when scaled to large environments like seaports. The main challenges are calibration and localization in obstructed conditions, which are common in logistics environments. Traditional calibration methods, dependent on line-of-sight (LoS), are slow, costly, and unreliable in seaports and warehouses, making large-scale localization a significant pain point in the industry. To overcome these challenges, we propose a UWB-LiDAR fusion-based calibration and one-shot localization framework. Our method uses Gaussian Processes to estimate anchor position from continuous-time LiDAR Inertial Odometry with sampled UWB ranges. This approach ensures accurate and reliable calibration with just one round of sampling in large-scale areas, I.e., 600x450 square meter. With the LoS issues, UWB-only localization can be problematic, even when anchor positions are known. We demonstrate that by applying a UWB-range filter, the search range for LiDAR loop closure descriptors is significantly reduced, improving both accuracy and speed. This concept can be applied to other loop closure detection methods, enabling cost-effective localization in large-scale warehouses and seaports. It significantly improves precision in challenging environments where UWB-only and LiDAR-Inertial methods fall short, as shown in the video (https://youtu.be/oY8jQKdM7lU). We will open-source our datasets and calibration codes for community use.