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Autonomous 3D modeling for robot arm based scanning

机译:基于机器人手臂的扫描的自主3D建模

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摘要

Precise 3D modeling of a workpiece is essential in many industrial applications, such as workpiece localization and inspection. However, the limits of sensor fields of view (FoV), object self-occlusions, and robot arm footprints demand a proper selection of scanning paths and views. In this paper, we propose an autonomous modeling scheme using a next best view (NBV) algorithm based on an adaptive structured light system, where projection patterns are adjusted in real time to achieve high-resolution point clouds with high efficiency. Moreover, a probabilistic method is developed to utilize the surrounding environment information for collision-free path planning. Our results show the system can achieve a 3D reconstruction of workpieces with better completeness, quality and a less working distance in total.
机译:在许多工业应用中,例如工件定位和检查,精确的工件3D建模至关重要。但是,传感器视场(FoV),对象自遮挡和机器人手臂足迹的限制要求对扫描路径和视场进行适当选择。在本文中,我们提出了一种基于自适应结构光系统的使用次最佳视图(NBV)算法的自主建模方案,其中实时调整投影模式以实现高分辨率的高效率点云。此外,开发了一种概率方法来利用周围环境信息进行无碰撞路径规划。我们的结果表明,该系统可以实现工件的3D重构,具有更好的完整性,质量和更少的总工作距离。

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