Improvement of Door Recognition Algorithm using Lidar and RGB-D camera for Mobile Manipulator

Taehyeon Kim, Minwoo Kang, Sumin Kang, D. Kim
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引用次数: 3

Abstract

The characteristics of mobile manipulator, which can perform various tasks in dynamic environments, have the advantage of driving and doing diverse tasks in large indoor environments with complex structures such as high-rise buildings. However, in order to efficiently navigate in such environments, mapping process containing information about diverse objects that robot can interact with is essential. Among these objects, door is of great importance, but door recognition is challenge because there are doors of various structures and sizes even in single indoor environment. This paper proposes an improvement of door recognition algorithm for mobile manipulator robot using RGB-D camera attached to end effector of manipulator and Lidar of mobile platform. Basically, laser scan data from Lidar is processed by line fitting algorithm and vision data from RGB-D camera is processed by YOLOv3. The process by laser scan data enables the first door recognition. And Additional recognition through vision data is possible by controlling the manipulator according to the weights given by the first recognition. The proposed algorithm has been verified in a simulation environment based on real-world, and we confirmed that it has a higher recognition success rate compared to traditional algorithms.
基于激光雷达和RGB-D摄像头的移动机械手门识别算法改进
可在动态环境中执行各种任务的移动机械手的特点,在高层建筑等结构复杂的大型室内环境中具有驱动和执行多种任务的优势。然而,为了在这样的环境中有效地导航,包含机器人可以与之交互的各种物体信息的映射过程是必不可少的。在这些物体中,门是非常重要的,但门的识别是一个挑战,因为即使在单一的室内环境中,也存在各种结构和大小的门。本文利用机械手末端执行器的RGB-D摄像头和移动平台的激光雷达,改进了移动机械手的门识别算法。基本上,激光雷达的激光扫描数据采用线拟合算法处理,RGB-D相机的视觉数据采用YOLOv3处理。该过程通过激光扫描数据实现首门识别。根据第一次识别给出的权值对机械手进行控制,可以实现视觉数据的附加识别。该算法在基于现实世界的仿真环境中进行了验证,与传统算法相比,该算法具有更高的识别成功率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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