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CLC number: TP13

On-line Access: 2021-02-01

Received: 2019-08-31

Revision Accepted: 2019-10-09

Crosschecked: 2020-05-18

Cited: 0

Clicked: 3188

Citations:  Bibtex RefMan EndNote GB/T7714

 ORCID:

Wei Li

https://orcid.org/0000-0001-8446-5427

Rong Xiong

https://orcid.org/0000-0001-9318-9014

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Frontiers of Information Technology & Electronic Engineering  2021 Vol.22 No.2 P.141-154

http://doi.org/10.1631/FITEE.1900460


A hybrid visual servo control method for simultaneously controlling a nonholonomic mobile and a manipulator


Author(s):  Wei Li, Rong Xiong

Affiliation(s):  State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   li_wei_666@163.com, rxiong@zju.edu.cn

Key Words:  Mobile manipulation, Hybrid visual servo, Eye-in-hand, Global Jacobian, Kalman filter


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Wei Li, Rong Xiong. 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): 141-154.

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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 hybrid visual servo (HVS) control rules. mobile manipulation 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 mobile manipulation robot. We propose an HVS motion control method for a mobile manipulation 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 mobile manipulation robot, the global Jacobian 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 mobile manipulation robot. To avoid the position error caused by observation, we also introduce the kalman filter to correct the positions and orientations of the end of the manipulator. Finally, the proposed algorithm is validated on a mobile manipulation platform consisting of a Bulldog chassis, a UR5 robotic arm, and a ZED camera.

一种同时控制非完整约束底盘和机械臂的混合视觉伺服方法


李玮,熊蓉
浙江大学工业控制技术国家重点实验室,中国杭州市,310027

摘要:视觉伺服控制规则是指利用机器人上所安装相机获取的图像数据进行机器人运动规划的控制方法,通常分为基于图像的视觉伺服、基于位置的视觉伺服和混合视觉伺服(HVS)控制规则。移动操作可扩大机械臂的工作范围和灵活性,但目前将视觉伺服控制应用于完整移动作业机器人运动的研究较少。本文提出一种面向6自由度机械臂与非完整移动基座组合构成的移动操作机器人HVS运动控制方法。基于移动操作机器人的运动学微分方程,推导了整个机器人的全局雅可比矩阵,进而结合位置信息和视觉图像信息推导了HVS控制方程。夹持器和目标之间的距离是通过安装在夹持器上的摄像机观察标记来计算的,并计算了在图像坐标系中标记特征点位置与期望位置之间的差异。将这些差异代入控制方程,可得到移动操作机器人各自由度的速度控制规律。为避免由观测引起的位置误差,引入卡尔曼滤波来校正机械臂末端的位置和方向。最后,在一台由Bulldog底盘、UR5机械臂和ZED相机组成的移动操作平台上进行了实验验证。

关键词:移动作业;混合视觉伺服;眼在手上;全局雅可比;卡尔曼滤波

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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