Abstract
Indoor pedestrian localization measurement is a hot topic and is widely used in indoor navigation and unmanned devices. PDR (Pedestrian Dead Reckoning) is a low-cost and independent indoor localization method, estimating position of pedestrians independently and continuously. PDR fuses the accelerometer, gyroscope and magnetometer to calculate relative distance from starting point, which is mainly composed of three modules: step detection, stride length estimation and heading calculation. However, PDR is affected by cumulative error and can only work in two-dimensional planes, which makes it limited in practical applications. In this paper, a novel localization method V-PDR is presented, which combines VPR (Visual Place Recognition) and PDR in a loosely coupled way. When there is error between the localization result of PDR and VPR, the algorithm will correct the localization of PDR, which significantly reduces the cumulative error. In addition, VPR recognizes scenes on different floors to correct floor localization due to vertical movement, which extends application scene of PDR from two-dimensional planes to three-dimensional spaces. Extensive experiments were conducted in our laboratory building to verify the performance of the proposed method. The results demonstrate that the proposed method outperforms general PDR method in accuracy and can work in three-dimensional space.
Highlights
Location information and location-based services are always hot topics
To verify the advantages of the proposed V-Pedestrian dead reckoning (PDR) algorithm compared with the traditional PDR algorithm in indoor positioning and to verify the feasibility of the vision-aided PDR (V-PDR) algorithm in three-dimensional space, the experiment was divided into two parts
The second was to verify the advantage of the proposed V-PDR model compared to the traditional PDR model, which included comparing the positioning results between the
Summary
In complex indoor environments, the satellite signals received by users is so weak that the GNSS-based positioning method will fail, which makes people turn to other effective techniques to obtain accurate the information of indoor location. Indoor localization methods can be divided into five categories: triangulation, sensing, recognition, fingerprint and DR (dead reckoning) [2] In these methods, RFID, Bluetooth, IR and WLAN require deploying additional equipment, resulting in an increased cost. DR does not rely on external environments and additional equipment, which can gain high accuracy in a short time. It achieves low-cost and independent localization through processing outputs of inertial sensors. Limited by cumulative error of gyroscopes, the positioning error will gradually increase when working
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