Novel LiDAR-assisted UWB positioning compensation for indoor robot localization

Abstract

In order to improve the localization error of the traditional ultra wide band (UWB) localization method, a novel light detection and ranging (LiDAR)-assisted UWB positioning compensation for indoor robot localization will be designed in this work. In details, two extended Kalman filters (EKFs) are employed. One is for providing a UWB-based position which is fused from the distances from reference nodes of UWB (URNs) to the target robot. And the data fusion models for the two EKFs will be derived. The other one is used to estimate the UWB position error by using the difference between the UWB and LiDAR-based distances. The test results show that the LiDAR-assisted UWB positioning compensation is effective to reduce the UWB localization error.