论文标题
绘制以下内容：2D LIDAR在室内动态环境中使用人跟踪器
Mapping While Following: 2D LiDAR SLAM in Indoor Dynamic Environments with a Person Tracker
论文作者
论文摘要
2D激光雷达的大满贯（同时定位和映射）由于其稳定性和灵活性而广泛用于室内环境中。但是，它的映射过程通常是在静态环境中操作的操作，而室内环境通常会充满动态的对象（例如人）。由于动态对象而引起的嘈杂点的生成图通常不完整且变形。为了解决这个问题，我们提出了一个基于2D-LIDAR的SLAM的框架，而无需手动控制，该框架有效地排除了动态对象（人），并简化了机器人映射环境的过程。该框架包括三个部分：人们跟踪，过滤和关注。我们在室内环境中使用两种经典2D-LIDAR的SLAM算法的实验中验证了我们提出的框架。结果表明，该框架有效地处理动态对象并减少映射误差。
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.
