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Robot arm manipulation using depth-sensing camera and inverse kinematics

机译:使用深度感应摄像机和反向运动学的机器人手臂操纵

摘要

Robotic arms can be controlled by human operators using different types of controllers or manipulators. For example, a Titan IV robot arm can be mounted on a ROUV (remotely operated underwater vehicle) for seafloor operation and can then be remotely controlled by a sophisticated manipulator, a “Master Controller”. An operator needs a lot of training with this type of controller before they could apply their skills manipulating real robot arms in the field. There are, however, simulators like GRI Simulations Inc.’s manipulator trainer which help a user train virtually on a particular robotic arm using either a master controller or a joystick. Compared to joysticks, master controllers are much more sophisticated and expensive devices. On the other hand, joysticks are not as convenient as controller mechanisms, since they are more generic products and do not map the functionalities of master controllers as well as the custom master controllers.udThis thesis presents a new technique to manipulate a robotic arm which uses an inexpensive depth-camera to capture the user input and inverse kinematics to define the motion of the robotic arm. Along with the easier manipulation of the robotic arm, the presented technique also adds some gesture commands to control the end-effector which makes the interaction more intuitive. To test the efficacy and efficiency of the proposed method, a user study was conducted in which 18 participants were asked to perform two placement tasks using a keyboard, a joystick and the depth-camera based interface. The presented technique is inexpensive and the results of the study suggest the technique is a good option for controlling robot arms with configurations similar to that of the Titan IV.
机译:人工操作人员可以使用不同类型的控制器或操纵器来控制机械臂。例如,Titan IV机械臂可以安装在ROUV(远程操作的水下航行器)上以进行海底操作,然后可以由复杂的操纵器“主控制器”进行远程控制。操作员需要大量使用此类控制器进行的培训,然后才能在现场应用其技能来操纵真正的机器人手臂。但是,还有诸如GRI Simulations Inc.的机械手训练器之类的模拟器,它可以帮助用户使用主控制器或操纵杆在特定的机械手臂上进行虚拟训练。与操纵杆相比,主控制器是更为复杂和昂贵的设备。另一方面,操纵杆不像控制器机制那样方便,因为它们是通用产品,不能映射主控制器和自定义主控制器的功能。 ud本文提出了一种操纵机器人手臂的新技术。使用便宜的深度相机来捕获用户输入,并使用反向运动学来定义机械臂的运动。除了更容易操纵机械臂之外,提出的技术还添加了一些手势命令来控制末端执行器,从而使交互更加直观。为了测试该方法的有效性和效率,进行了一项用户研究,其中要求18名参与者使用键盘,操纵杆和基于深度相机的界面执行两项放置任务。提出的技术价格便宜,研究结果表明,该技术是控制类似于Titan IV的配置的机械手的不错选择。

著录项

  • 作者

    Mishra Akhilesh Kumar;

  • 作者单位
  • 年度 2015
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  • 原文格式 PDF
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