Relative ultra-wideband based localization of multi-robot systems with kinematic extended Kalman filter

TL;DR

This paper enhances multi-robot relative localization by integrating UWB measurements with a kinematic extended Kalman filter, improving accuracy in position and angle estimation through simulation validation.

Contribution

It introduces a novel fusion of UWB telemetry and kinematic modeling within an extended Kalman filter for improved multi-robot localization.

Findings

Enhanced relative distance and angle accuracy in simulations

Performance increases with shared control inputs

Validated improvements over previous methods

Abstract

Localization plays a critical role in the field of distributed swarm robotics. Previous work has highlighted the potential of relative localization for position tracking in multi-robot systems. Ultra-wideband (UWB) technology provides a good estimation of the relative position between robots but suffers from some limitations. This paper proposes improving the relative localization functionality developed in our previous work, which is based on UWB technology. Our new approach merges UWB telemetry and kinematic model into an extended Kalman filter to properly track the relative position of robots. We performed a simulation and validated the improvements in relative distance and angle accuracy for the proposed approach. An additional analysis was conducted to observe the increase in performance when the robots share their control inputs.