Object Grabbing of Robotic Arm Based on OpenMV Module Positioning

Abstract

Many robotic arms today incorporate machine vision to enhance the task diversity of robotic arms. In this paper a robotic arm grabbing system based on the camera is introduced. Firstly, the OpenMV module is used to integrate the machine vision recognition and position to make the robotic manipulator have the function of autonomous grasping. a normalized cross-correlation template matching algorithm is used to realize the recognition of the simulated chicken model, and the position information is calculated. Secondly, the D-H parameter method is used to describe the robotic arm hardware structure, and the inverse kinematics equations are obtained. Finally, after the embedded microcontroller obtains the position information into six joint angles through solving the inverse kinematics equations, the stepper motor drivers control the stepper motors on the joints of the robotic arm by means of the pulse output, so that the robotic arm moves to the chicken model position. The experimental test shows that the system can complete the grasping task of the chicken model.