Robot-assisted RSSI data collection for indoor fingerprint-based positioning

Indoor positioning has diverse applications in public safety, industry, and healthcare [ 1 ]. This paper presents a robot-assisted data collection method to overcome the inefficiencies of conventional smartphone-based approaches in indoor positioning. By integrating advanced hardware and software optimizations, the robot achieves efficient and comprehensive Wi-Fi RSSI (Received Signal Strength Indicator) data acquisition at reference points (RPs). Experimental results demonstrate that the robot-assisted system achieves a positioning accuracy of 91.92%, improving accuracy by 1.8% compared to the smartphone-based method [ 2 ], while reducing data collection time by 59%. The results validate the proposed method’s efficiency, systematization, and effectiveness in improving indoor positioning.