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Frontiers of Information Technology & Electronic Engineering

2021, Volume 22,  Issue 2, Pages 141-286
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    A hybrid visual servo control method for simultaneously controlling a nonholonomic mobile and a manipulator

    浙江大学工业控制技术国家重点实验室,中国杭州市,310027

    Received:2019-08-31 Accepted: 2021-02-01 Available online:2021-02-01
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    10.1631/FITEE.1900460
    Cite this article
    Wei Li, Rong Xiong,li_wei_666@163.com,rxiong@zju.edu.cn.A hybrid visual servo control method for simultaneously controlling a nonholonomic mobile and a manipulator[J].Frontiers of Information Technology & Electronic Engineering,2021,22(2):141-286.

    Abstract

    Visual servo control rules that refer to the control methods of robot motion planning using image data acquired from the camera mounted on the robot have been widely applied to the motion control of robotic arms or mobile robots. The methods are usually classified as image-based visual servo, position-based visual servo, and (HVS) control rules. enhances the working range and flexibility of robotic arms. However, there is little work on applying visual servo control rules to the motion of the whole robot. We propose an HVS motion control method for a robot which combines a six-degree-of-freedom (6-DOF) robotic arm with a nonholonomic mobile base. Based on the kinematic differential equations of the robot, the matrix of the whole robot is derived, and the HVS control equation is derived using the whole Jacobian matrix combined with position and visual image information. The distance between the gripper and target is calculated through the observation of the marker by a camera mounted on the gripper. The differences between the positions of the markers ’ feature points and the expected positions of them in the image coordinate system are also calculated. These differences are substituted into the control equation to obtain the speed control law of each degree of freedom of the robot. To avoid the position error caused by observation, we also introduce the to correct the positions and orientations of the end of the manipulator. Finally, the proposed algorithm is validated on a platform consisting of a Bulldog chassis, a UR5 robotic arm, and a ZED camera.

    Keywords

    移动作业;混合视觉伺服;眼在手上;全局雅可比;卡尔曼滤波
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