BLE Beacon-based floor detection for mobile robots in a multi-floor automation Laboratory

As an important task of multi-floor localization, floor detection has elicited great attention. Wireless infrastructures like Wi-Fi and Bluetooth low-energy play important roles in floor detection. However, most floor detection research studies tend to focus on data modeling but pay little attention to the data collection system, which is the basis of wireless infrastructure-based floor detection. In fact, the floor detection task can be greatly simplified with proper data collection system design. In this paper, a floor detection solution is developed in a multi-floor life science automation lab. A data collection system consisting of BLE beacons, receiver node, and IoT cloud is provided. The features of the BLE beacon under different settings are evaluated in detail. A mean filter is designed to deal with the fluctuation of the RSSI data. A simple floor detection method without a training process was implemented and evaluated in more than 100 floor detection tests. The time delay and floor detection accuracy under different settings are discussed. Finally, floor detection is evaluated on the H20 multi-floor transportation robot. Two sensor nodes are installed on the robot at different heights. The floor detection performance with different installation heights is discussed. The experimental results indicate that the proposed floor detection method provides floor detection accuracy of 0.9877 to 1 with a time delay of 5 s.