人追従で動く屋内環境を2D LiDAR SLAMで地図化するフレームワーク
Mapping While Following: 2D LiDAR SLAM in Indoor Dynamic Environments with a Person Tracker
2D LiDAR SLAMで人を追従しながら移動し、動的物体を除去して歪みの少ない地図を作る枠組みを提案し、2種類のSLAMアルゴリズムで有効性を検証した。
著者: Hanjing Ye, Guangcheng Chen, Weinan Chen, Li He, Yisheng Guan, Hong Zhang
分類: cs.RO
原文アブストラクト
2D LiDAR SLAM (Simultaneous Localization and Mapping) is widely used in indoor environments due to its stability and flexibility. However, its mapping procedure is usually operated by a joystick in static environments, while indoor environments often are dynamic with moving objects such as people. The generated map with noisy points due to the dynamic objects is usually incomplete and distorted. To address this problem, we propose a framework of 2D-LiDAR-based SLAM without manual control that effectively excludes dynamic objects (people) and simplify the process for a robot to map an environment. The framework, which includes three parts: people tracking, filtering and following. We verify our proposed framework in experiments with two classic 2D-LiDAR-based SLAM algorithms in indoor environments. The results show that this framework is effective in handling dynamic objects and reducing the mapping error.
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