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Orthogonal Image Features for Visual Servoing of a 6-DOF Manipulator With Uncalibrated Stereo Cameras

机译:带有未经校准的立体摄像机的6自由度机械手视觉伺服的正交图像功能

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We present an approach to control a 6-degree-of-freedom (DOF) manipulator using an uncalibrated visual servoing (VS) approach that addresses the challenges of choosing proper image features for target objects and designing a VS controller to enhance the tracking performance. The main contribution of this paper is the definition of a new virtual visual space (image space). A novel stereo camera model employing virtual orthogonal cameras is used to map 6-D poses from to this . Each component of the 6-D pose vector defined in this virtual visual space is linearly independent, leading to a full-rank , which allows avoiding classical problems, such as image space singularities and local minima. Furthermore, the control for rotational and translational motion of robot is decoupled due to the diagonal image Jacobian. Finally, simulation results with an eye-to-hand robotic system confirm the improvement in controller stability and motion performance with respect to conventional VS approaches. Experimental results on a 6-DOF industrial robot are provided to illustrate the effectiveness of the proposed method and the feasibility of using this method in practical scenarios.
机译:我们提出了一种使用未校准的视觉伺服(VS)方法控制6自由度(DOF)机械手的方法,该方法解决了为目标对象选择合适的图像特征并设计VS控制器以增强跟踪性能的挑战。本文的主要贡献是对新的虚拟视觉空间(图像空间)的定义。使用虚拟正交相机的新型立体相机模型用于从中映射6D姿势。在此虚拟视觉空间中定义的6D姿态向量的每个分量都是线性独立的,从而导致了全等级,这可以避免经典问题,例如图像空间奇异性和局部极小值。此外,由于对角线图像雅可比行列式,机器人的旋转和平移运动控制被解耦。最后,与手动机器人系统的仿真结果证实了相对于传统VS方法,控制器稳定性和运动性能的提高。提供了六自由度工业机器人的实验结果,以说明该方法的有效性以及在实际场景中使用该方法的可行性。

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