NR-UIO: NLOS-Robust UWB-Inertial Odometry Based on Interacting Multiple Model and NLOS Factor Estimation

Abstract

Recently, technology utilizing ultra-wideband (UWB) sensors for robot localization in an indoor environment where the global navigation satellite system (GNSS) cannot be used has begun to be actively studied. UWB-based positioning has the advantage of being able to work even in an environment lacking feature points, which is a limitation of positioning using existing vision- or LiDAR-based sensing. However, UWB-based positioning requires the pre-installation of UWB anchors and the precise location of coordinates. In addition, when using a sensor that measures only the one-dimensional distance between the UWB anchor and the tag, there is a limitation whereby the position of the robot is solved but the orientation cannot be acquired. To overcome this, a framework based on an interacting multiple model (IMM) filter that tightly integrates an inertial measurement unit (IMU) sensor and a UWB sensor is proposed in this paper. However, UWB-based distance measurement introduces large errors in multipath environments with obstacles or walls between the anchor and the tag, which degrades positioning performance. Therefore, we propose a non-line-of-sight (NLOS) robust UWB ranging model to improve the pose estimation performance. Finally, the localization performance of the proposed framework is verified through experiments in real indoor environments.

A benchmark analysis of data‐driven and geometric approaches for robot ego‐motion estimation

“…Odometry is certainly one of the most crucial components of robotic and autonomous platforms, which may exploit different sensors for ego-motion estimation (Almeida & Santos, 2013;Hyun & Myung, 2021) in a variety of applications, both ground (Geiger et al, 2012) and aerial (Burri et al, 2016;Schubert et al, 2018).…”

“…Odometry is certainly one of the most crucial components of robotic and autonomous platforms, which may exploit different sensors for ego‐motion estimation (Almeida & Santos, 2013; Hyun & Myung, 2021) in a variety of applications, both ground (Geiger et al, 2012) and aerial (Burri et al, 2016; Schubert et al, 2018). In particular, visual odometry (VO) has been the focus of countless research efforts in the last years (Bresson et al, 2017; Cadena et al, 2016; Scaramuzza & Fraundorfer, 2011), as one of the fundamental steps of vision‐based localization, mapping and navigation systems.…”

Fusion localization for indoor airplane inspection using visual inertial odometry and ultrasonic RTLS

“…Particularly, UWB employs impulse radio frequency carrier-less signals, allowing it to measure time between transmit and receive with high accuracy 1 . However, UWB or ultrasonic RTLS can also be affected by signal degradation due to obstacles in the hangar, multipath effect near airplane surfaces, or signal interference from avionic equipment in an airport 1,2 .…”