BLE beacon-based floor detection for mobile robots in a multi-floor automation laboratory

作     者：Haiping Wu Hui Liu Thomas Roddelkopf Kerstin Thurow Haiping Wu;Hui Liu;Thomas Roddelkopf;Kerstin Thurow

作者机构：Institute of Artificial Intelligence&Robotics(IAIR)Key Laboratory of Traffic Safety on Track of Ministry of EducationSchool of Traffic and Transportation EngineeringCentral South UniversityChangshaHunan 410075China Center of Life Science Automation(celisca)18119 Rostoc kGerman y Institute of Automation(IAT)University Rostock18119 RostockGermany 

出 版 物：《Transportation Safety and Environment》 (交通安全与环境（英文）)

年 卷 期：2024年第6卷第2期

页      面：114-121页

核心收录：

学科分类：08[工学] 0838[工学-公安技术] 

基　　金：the Synergy Project ADAM(Au-tonomous Discovery of Advanced Materials)funded by the Eu-ropean Research Council(Grant No.856405) 

主　　题：BLE beacon floor detection multi-floor automation transportation robot 

摘      要：As an important task of multi-floor localization,floor detection has elicited great *** infrastructures like Wi-Fi and Bluetooth Low Energy(BLE)play important roles in floor ***,most floor detection research tends to focus on data modelling but pays little attention to the data collection system,which is the basis of wireless infrastructure-based floor *** fact,the floor detection task can be greatly simplified with proper data collection system *** this paper,a floor detection solution is developed in a multi-floor life science automation lab.A data collection system consisting of BLE beacons,a receiver node and an Internet of Things(IoT)cloud is *** features of the BLE beacon under different settings are evaluated in detail.A mean filter is designed to deal with the fluctuation of the received signal strength indicator data.A simple floor detection method without a training process was implemented and evaluated in more than 100 floor detection *** time delay and floor detection accuracy under different settings are ***,floor detection is evaluated on the H20 multi-floor transportation *** sensor nodes are installed on the robot at different *** floor detection performance with different installation heights is *** experimental results indicate that the proposed floor detection method provides floor detection accuracy of 0.9877 to 1 with a time delay of 5s.