Geometric Calibration of Rotational Vision System for Dynamic Exterior Orientation

Rotational Vision System(RVS)is a common active vision system with only rotational degrees of freedom.Usually,the degree of freedom for rotation is provided by the turntable and pan head.Or the hand to eye(EIH)structure in articulated arm robots.Due to assembly deviations and manufacturing accuracy limitations,the ideal assumption that the rotation axis is fully aligned with the coordinate axis of the local camera is mostly violated.To address this issue,we propose a generalized deviation model that specifies a rotation axis that connects the rotational motion of the platform with the external orientation(EO)of the camera.On this basis,we propose a heuristic estimation algorithm to minimize global reprojection errors and fit circles in space under constraints of global optimization.The experiment shows that the translation and tilt average reprojection errors of dynamic EO reconstruction based on the reprojection error method are 0.14 and 0.08 pixels,respectively.In the absence of angle measurement,the results of the circle fitting method are similar to them(with a relative error of about 2%),meeting the application requirements of general visual measurement.

基于Halcon的工业机器人手眼标定方法研究

机器人手眼标定是机器人视觉技术的重要研究内容,基于Halcon所提供的标定板,充分考虑相机镜头径向畸变对手眼标定的影响,设计一种全新的、高精度、高效率的Eye-in-Hand手眼标定方法,该方法在标定了相机内外参数的同时也建立了相机图像坐标系与机器人基坐标系之间的相互转换关系,并通过实验进行了验证,其平移误差在1mm,旋转误差在1。以内。实验结果表明该方法具有较高的标定效率与较高的标定精度,可广泛应用于工业机器人视觉系统手眼标定中。

Uncalibrated visual servoing design for competitive networked robots

In this paper,a method with an eye-in-hand configuration is developed to hit targets during visual tracking for the TLS(Tele-Light Saber) game.It is not necessary to calibrate camera parameters and predict the trajectory of the moving object.Firstly,the expression of the image Jacobian matrix for the eye-in-hand configuration is proposed,and then an update law is designed to estimate the image Jacobian online.Furthermore,a control scheme is presented and the Lyapunov method is employed to prove asymptotic convergence of image errors.No assumption for the moving objects is needed.Finally,both simulation and experimental results are shown to support the approach in this paper.

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

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-degreeof-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.