Abstract
This paper proposes a method for determining a pedestrian’s indoor location based on an UWB (ultra-wideband) and vison fusion algorithm. Firstly, an UWB localization algorithm based on EKF (extended Kalman filter) is proposed, which can achieve indoor positioning accuracy of 0.3 m. Secondly, a method to solve scale ambiguity and repositioning of the monocular ORB-SLAM (oriented fast and rotated brief-simultaneous localization and mapping) algorithm based on EKF is proposed, which can calculate the ambiguity in real time and can quickly reposition when the vision track fails. Lastly, two experiments were carried out, one in a corridor with sparse texture and the other with the light brightness changing frequently. The results show that the proposed scheme can reliably achieve positioning accuracy on the order of 0.2 m; with the combination of algorithms, the scale ambiguity of monocular ORB-Slam can be solved, with the failed vision trace repositioned by UWB, and the positioning accuracy of UWB can be improved, making it suitable for pedestrian location in indoor environments with sparse texture and frequent light brightness changes.
Highlights
Indoor localization and navigation are considered an enabler for a variety of applications, such as guidance of passengers in airports, conference attendees, and visitors in shopping malls, hospitals, or office buildings [1]
The results show that the proposed scheme can reliably achieve positioning accuracy on the order of 0.2 m; with the combination of algorithms, the scale ambiguity of monocular ORB-Slam can be solved, with the failed vision trace repositioned by UWB, and the positioning accuracy of UWB can be improved, making it suitable for pedestrian location in indoor environments with sparse texture and frequent light brightness changes
At present, indoor positioning methods based on vision fail due to sparse textures, light that is too bright or too dark, and other factors
Summary
Indoor localization and navigation are considered an enabler for a variety of applications, such as guidance of passengers in airports, conference attendees, and visitors in shopping malls, hospitals, or office buildings [1]. Enhanced UAV indoor navigation through SLAM-augmented UWB localization was proposed, in which the SLAM-augmented UWB localization had a 90% quantile error of 13.9 cm, and it was shown that the method is capable of providing positioning data to the control system to allow for effective navigation of a drone in the environment. In this method, the odometer are used to estimate the altitude, and the flight area map is established through several flights [19]. The research contents, methods, and future improvements of the paper are summarized and analyzed
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