Automatic Detection of Valves with Disaster Response Robot on Basis of Depth Camera Information

Keishi Nishikawa, J. Ohya, T. Matsuzawa, A. Takanishi, H. Ogata, K. Hashimoto
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引用次数: 1

Abstract

In recent years, there has been an increasing demand for disaster response robots designed for working in disaster sites such as nuclear power plants where accidents have occurred. One of the tasks the robots need to complete at these kinds of sites is turning a valve. In order to employ robots to perform this task at real sites, it is desirable that the robots have autonomy for detecting the valves to be manipulated. In this paper, we propose a method that allows a disaster response robot to detect a valve, whose parameters such as position, orientation and size are unknown, based on information captured by a depth camera mounted on the robot. In our proposed algorithm, first the target valve is detected on the basis of an RGB image captured by the depth camera, and 3D point cloud data including the target is reconstructed by combining the detection result and the depth image. Second, the reconstructed point cloud data is processed to estimate parameters describing the target. Experiments were conducted on a simulator, and the results showed that our method could accurately estimate the parameters with a minimum error of 0.0230 m in position, 0.196 % in radius, and 0.00222 degree in orientation.
基于深度相机信息的灾害响应机器人阀门自动检测
近年来,为在核电站等发生事故的灾难现场工作而设计的灾难响应机器人的需求不断增加。在这些地方,机器人需要完成的任务之一是转动阀门。为了让机器人在实际现场执行这项任务,希望机器人能够自主检测要操作的阀门。在本文中,我们提出了一种方法,该方法允许灾难响应机器人根据安装在机器人上的深度相机捕获的信息检测位置,方向和尺寸等参数未知的阀门。该算法首先基于深度相机捕获的RGB图像对目标阀进行检测,并结合检测结果和深度图像重构包含目标的三维点云数据。其次,对重建的点云数据进行处理,估计描述目标的参数;仿真实验结果表明,该方法能够准确地估计参数,位置误差最小为0.0230 m,半径误差最小为0.196 %,方位误差最小为0.00222°。
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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