视觉伺服机械臂手机抓取最佳位姿检测

针对下水道、勾缝等狭窄位置的手机拾取的问题, 本文提出一种基于机器视觉的伺服机械臂抓取方法. 首先对机械臂eye-in-hand上的相机进行标定, 图像预处理及目标检测等, 在位姿检测中提出一种基于二维坐标系下手机位姿解算算法, 得出解算的最佳位姿角只与夹持点的像素坐标的差值有关, 其位姿角的大小决定了手抓旋转的角度. 实验用Matlab软件对位姿检测进行仿真分析, 其包括SURF不变特征点的目标检测实验和位姿解算实验, 最后用Rethink双臂机器人的右臂对手机进行抓取验证. 实验表明, 在误差允许范围内, 提出的算法具有一定的有效性, 其结果为伺服机械臂抓取手机提供良好的准确性.

Visual Servo Manipulator to Grab Mobile Phone of the Best Pose Detection

Aiming at the pickup of mobile phones in narrow locations such as sewers and jointing, this study proposes a method of servo mechanical arms for grabbing based on machine vision. Firstly, the camera on the eye-in-hand mechanical arm is calibrated, followed by image preprocessing and target detection. In the pose detection, we propose an algorithm to solve the pose of the mobile phones based on the two-dimensional coordinate system. It turns out that the best pose angle is only related to the difference in the pixel coordinates of the clamping point, and the size of the pose angle determines the rotation angle of the gripper. Then, the pose detection is simulated by Matlab, including target detection with SURF invariant feature points and pose calculation. Finally, the right arm of a two-armed Rethink robot grasps a mobile phone for verification. The results show that within the allowable error range, the proposed algorithm accurately guides the servo mechanical arms to grasp mobile phones.