BSL：基于ROS导航栈与盲点层的移动机器人考虑盲点的导航方法
BSL: Navigation Method Considering Blind Spots Based on ROS Navigation Stack and Blind Spots Layer for Mobile Robot
AI总结：
针对轮式机器人因环境拐角或障碍物形成盲点而可能与人或物体碰撞的问题，提出基于ROS导航栈、BSL局部代价地图层和增强DWA代价函数的导航方法，并经仿真与实验验证。
摘要：
本文针对轮式移动机器人，提出了一种基于机器人操作系统（ROS）导航栈和盲点层（BSL）的考虑盲点的导航方法。本文中，环境信息通过激光测距仪（LRF）和RGB-D相机进行识别。当环境中存在拐角或障碍物时会出现盲点；如果人或物体从这些盲点向机器人移动，可能导致碰撞。为防止此类碰撞，本文针对轮式移动机器人提出了一种基于BSL局部代价地图层的考虑盲点的导航方法。盲点通过利用RGB-D相机采集的环境数据进行估计。考虑这些盲点的导航方法通过实现BSL以及采用增强型动态窗口法代价函数的局部路径规划方法来实现。所提方法的有效性通过仿真和实验得到了进一步验证。
英文摘要：
This paper proposes a navigation method considering blind spots based on the robot operating system (ROS) navigation stack and blind spots layer (BSL) for a wheeled mobile robot. In this paper, environmental information is recognized using a laser range finder (LRF) and RGB-D cameras. Blind spots occur when corners or obstacles are present in the environment, and may lead to collisions if a human or object moves toward the robot from these blind spots. To prevent such collisions, this paper proposes a navigation method considering blind spots based on the local cost map layer of the BSL for the wheeled mobile robot. Blind spots are estimated by utilizing environmental data collected through RGB-D cameras. The navigation method that takes these blind spots into account is achieved through the implementation of the BSL and a local path planning method that employs an enhanced cost function of dynamic window approach. The effectiveness of the proposed method was further demonstrated through simulations and experiments.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
