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Simulation of detecting and climbing a ladder for a humanoid robot

机译:模拟和爬人形机器人的梯子的仿真

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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:摘要最近的DARPA挑战赛提出了一个工业事故场景,供类人机器人穿越并执行以人为本的任务。在挑战的第五阶段,机器人必须攀爬壁挂金属梯子。为了完成此任务,机器人必须在抓握和攀爬之前首先识别并定位梯子。本文使用来自模拟的Microsoft Kinect传感器的点云数据介绍了梯级的定位。它还介绍了使用PR2 Robot抓握和攀爬的操作员。基本方法是首先分割出背景平面。我们应用体素网格过滤器以加快计算速度。然后,使用RANSAC算法提取代表腿的线和内部梯级中线。垂直线将被丢弃,仅保留代表横档的线。计算线的中心是我们估算的梯级质心的位置。然后,我们可以将质心信息用于PR2抓取。

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