Evaluation of the Benefits of Zero Velocity Update in Decentralized EKF-Based Cooperative Localization Algorithms for GNSS-Denied Multi-Robot Systems

TL;DR

This paper evaluates how zero velocity updates enhance decentralized EKF-based localization accuracy in multi-robot systems operating without GNSS signals, demonstrating significant improvements through real-world and simulated experiments.

Contribution

It is the first to systematically assess the benefits of ZU in a decentralized EKF for multi-robot localization in GNSS-denied environments.

Findings

ZU improves 3D localization accuracy significantly.

Using ZU with simple heuristics enhances multi-robot localization.

Experimental results confirm the effectiveness of ZU in real and simulated environments.

Abstract

This paper proposes the cooperative use of zero velocity update (ZU) in a decentralized extended Kalman filter (DEKF) based localization algorithm for multi-robot systems. The filter utilizes inertial measurement unit (IMU), ultra-wideband (UWB), and odometry velocity measurements to improve the localization performance of the system in the presence of a GNSS-denied environment. The contribution of this work is to evaluate the benefits of using ZU in a DEKF-based localization algorithm. The algorithm is tested with real hardware in a video motion capture facility and a Robot Operating System (ROS) based simulation environment for unmanned ground vehicles (UGV). Both simulation and real-world experiments are performed to show the effectiveness of using ZU in one robot to reinstate the localization of other robots in a multi-robot system. Experimental results from GNSS-denied simulation and real-world environments show that using ZU with simple heuristics in the DEKF significantly improves the 3D localization accuracy.