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.

视觉伺服控制规则已广泛应用于机器人手臂或移动机器人的运动控制，该视觉伺服控制规则是指使用从安装在机器人上的摄像机获取的图像数据来进行机器人运动计划的控制方法。这些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。移动操纵增加了机械臂的工作范围和灵活性。但是，将视觉伺服控制规则应用于整个移动操纵机器人的动作方面的工作很少。我们提出了一种用于移动操纵机器人的HVS运动控制方法，该方法将六自由度（6-DOF）机器人手臂与非完整移动基座结合在一起。根据移动操纵机器人的运动学微分方程，推导出整个机器人的全局雅可比矩阵，并使用整个雅可比矩阵结合位置和视觉图像信息推导HVS控制方程。夹具与目标之间的距离是通过安装在夹具上的摄像机观察标记来计算的。还计算了标记特征点的位置与它们在图像坐标系中的预期位置之间的差异。将这些差异代入控制方程式以获得移动操纵机器人的每个自由度的速度控制律。为了避免观察引起的位置误差，我们还引入了卡尔曼滤波器来校正操纵器末端的位置和方向。最后，