WiFi指紋の類似度に基づく複数ロボット協調電波SLAM
Collaborative Radio SLAM for Multiple Robots based on WiFi Fingerprint Similarity
複数ロボットが収集したWiFi電波指紋とオドメトリを用いて軌道を集中最適化する協調SLAMを提案し、RSSとAP検出尤度を組み合わせた新たな類似度モデルで位置推定精度を向上させた。
著者: Ran Liu, Zhenghong Qin, Hua Zhang, Billy Pik Lik Lau, Khairuldanial Ismail, Achala Athukorala, Chau Yuen, Yong Liang Guan, U-Xuan Tan
分類: cs.RO
原文アブストラクト
Simultaneous Localization and Mapping (SLAM) enables autonomous robots to navigate and execute their tasks through unknown environments. However, performing SLAM in large environments with a single robot is not efficient, and visual or LiDAR-based SLAM requires feature extraction and matching algorithms, which are computationally expensive. In this paper, we present a collaborative SLAM approach with multiple robots using the pervasive WiFi radio signals. A centralized solution is proposed to optimize the trajectory based on the odometry and radio fingerprints collected from multiple robots. To improve the localization accuracy, a novel similarity model is introduced that combines received signal strength (RSS) and detection likelihood of an access point (AP). We perform extensive experiments to demonstrate the effectiveness of the proposed similarity model and collaborative SLAM framework.
