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Gesture-World Environment Technology for Mobile Manipulation - Remote Control System of a Robot with Hand Pose Estimation

机译:用于移动操作的手势世界环境技术-具有手部姿势估计的机器人远程控制系统

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摘要

The purpose of this paper is to propose a remote-controlled robot system capable of accurate highspeed performance of the same operation strictly conforming to human operator movement without sensors or special control means. We specifically intend to implement high-precision high-speed 3D hand pose estimation enabling a remote-controlled robot to be operated using two cameras installed loosely orthogonally using one ordinary PC. The two cameras have their own database. Once sequential hand images are shot at high speed, the system starts selecting one database with bigger size of hand region in each recorded image. Coarse screening then proceeds based on proportional hand image information roughly corresponding to wrist rotation or thumb or finger extension. Finally, a detailed search is done for similarity among selected candidates. Experiments show that mean and standard deviation scores of errors in estimated angles at the proximal interphalangeal (PIP) index are 0.45 ± 14.57 and at the carpometacarpal (CM) thumb 4.7 ± 10.82, respectively, indicating it as a high-precision 3D hand pose estimation. Remote control of a robot with the proposed vision system shows high performance as well.
机译:本文的目的是提出一种远程控制机器人系统,该系统在没有传感器或特殊控制装置的情况下,能够严格遵守人类操作者的动作,能够精确地执行同一操作的高速性能。我们特别打算实现高精度的3D高速手势估计,以使远程控制机器人能够使用一台普通PC正交安装的两个摄像机来操作。这两个摄像机都有自己的数据库。一旦高速拍摄了连续的手部图像,系统便开始在每个记录的图像中选择一个具有较大手部区域大小的数据库。然后基于大致对应于手腕旋转或拇指或手指伸展的比例手图像信息进行粗筛。最后,对所选候选者之间的相似性进行详细搜索。实验表明,在指间近端(PIP)指数和腕掌(CM)拇指上的估计角度误差的平均和标准偏差分数分别为0.45±14.57和4.7±10.82,表明它是高精度的3D手部姿势估计。使用建议的视觉系统对机器人进行远程控制也显示出高性能。

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