LiDARとWi-Fiの冗長・疎結合統合による自律移動ロボットのロバストなグローバル自己位置推定
Redundant and Loosely Coupled LiDAR-Wi-Fi Integration for Robust Global Localization in Autonomous Mobile Robotics
LiDAR記述子とWi-Fiフィンガープリントを組み合わせ、各予測の信頼度を考慮して統合することで、GNSSが使えない環境でもロバストに自己位置を推定するフレームワークを提案した。
著者: Nikolaos Stathoulopoulos, Emanuele Pagliari, Luca Davoli, George Nikolakopoulos
分類: cs.RO
原文アブストラクト
This paper presents a framework addressing the challenge of global localization in autonomous mobile robotics by integrating LiDAR-based descriptors and Wi-Fi fingerprinting in a pre-mapped environment. This is motivated by the increasing demand for reliable localization in complex scenarios, such as urban areas or underground mines, requiring robust systems able to overcome limitations faced by traditional Global Navigation Satellite System (GNSS)-based localization methods. By leveraging the complementary strengths of LiDAR and Wi-Fi sensors used to generate predictions and evaluate the confidence of each prediction as an indicator of potential degradation, we propose a redundancy-based approach that enhances the system's overall robustness and accuracy. The proposed framework allows independent operation of the LiDAR and Wi-Fi sensors, ensuring system redundancy. By combining the predictions while considering their confidence levels, we achieve enhanced and consistent performance in localization tasks.
