UVIP: Robust UWB aided Visual-Inertial Positioning System for Complex Indoor Environments

Bo Yang, Jun Li, Hong Zhang

Abstract: Indoor positioning without GPS is a challenge task, especially, in complex scenes or when sensors fail. In this paper, we develop an ultra-wideband aided visual-inertial positioning system (UVIP) which aims to achieve accurate and robust positioning results in complex indoor environments. To this end, a point-line-based stereo visual-inertial odometry (PL-sVIO) is firstly designed to improve the positioning accuracy in structured or low-textured scenarios by making use of line features. Secondly, a loop closure method is proposed to suppress the drift of PL-sVIO based on image patch features described by a CNN for handing the situation of a large environment and viewpoint variation. Thirdly, an accurate relocalization approach is presented for the case when the visual sensor fails. In this scheme, a top-to-down matching strategy from image to point and line features is presented to improve relocalization performance. Finally, the UWB sensor is combined with the visual-inertial system to further improve the accuracy and robustness of the positioning system and provide the results in a fixed reference frame. Thus, desirable real-time positioning results are derived for complex indoor scenes. Evaluations on challenging public datasets and real-world experiments are conducted to demonstrate that the proposed UVIP can provide more accurate and robust positioning results in complex indoor environments, even in the case when the visual sensor fails or in the absence of UWB anchors.