An algorithm for real-time restructuring of a ranging-based localization network

TL;DR

This paper introduces a real-time adaptive algorithm that dynamically restructures a range-based localization network using a mobile UWB sensor to enhance robot localization accuracy in challenging environments.

Contribution

It presents a novel real-time restructuring algorithm that optimizes localization network configuration using a mobile anchor to improve accuracy in harsh conditions.

Findings

Algorithm effectively improves localization accuracy in experiments.

Real-time network restructuring reduces localization error.

Mobile anchor movement enhances robustness in challenging environments.

Abstract

This paper presents a method to improve the localization accuracy of robots operating in a range-based localization network. The method is favorable especially when the robots operate in harsh environments where the access to a robust and reliable localization system is limited. A state estimator is used for a six degree of freedom object using inertial sensors as well as an Ultra-wideband (UWB) range measurement sensor. The estimator is incorporated into an adaptive algorithm, improving the localization quality of an agent by using a mobile UWB ranging sensor, where the mobile anchor moves to improve localization quality. The algorithm reconstructs localization network in real-time to minimize the determinant of the covariance matrix in the sense of least square error. Finally, the proposed algorithm is experimentally validated in a network consisting of one mobile and four fixed anchors.