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Simulation of detecting and climbing a ladder for a humanoid robot

机译:用于人形机器人梯子的仿真

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ABSTRACT The most recent DARPA challenge presents an industrial accident scenerio for a humanoid robot to traverse and then perform human oriented tasks. In the fifth stage of the challenge, the robot must climb a wall mounted metal rung ladder. To accomplish this task, the robot must first recognize and localize the ladder prior to grasping and climbing. This paper presents the localization of the rungs using point cloud data from a simulated Microsoft Kinect sensor. It also presents grasping and climbing manuveur using PR2 Robot. The basic approach is to first segment out the background planes. We apply a voxel grid filter to make the computation faster. Then using the RANSAC algorithm, lines that represent the legs and the interior rung midline are extracted. Vertical lines are thrown away and only the lines that represent the rungs are retained. The center of the computed line is our estimated location for the rung centroid. We then can use the centroid information for the PR2 grasping.
机译:摘要最新的DARPA挑战是人类机器人遍历的工业事故场景,然后执行人类面向的任务。在挑战的第五阶段,机器人必须爬上壁挂式金属梯梯。为了完成这项任务,机器人必须首先在抓住和攀爬之前识别和本地化梯子。本文介绍了使用来自模拟Microsoft Kinect传感器的点云数据的梯级的本地化。它还使用PR2机器人掌握抓住和攀爬制造商。基本方法是首先分割背景飞行。我们应用Voxel网格过滤器以使计算更快。然后使用Ransac算法,提取代表腿部和内部梯级中线的线。垂直线被抛弃,只保留表示梯级的线。计算线的中心是梯度质心的估计位置。然后,我们可以使用PR2 GRASPing的质心信息。

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