Design of a Four-Axis Robot Arm System Based on Machine Vision

With the concept of industrial automation gradually being put forward, the four-axis robotic arm is gradually being applied in industrial production environments due to its advantages such as a stable structure, easy maintenance, and expandability. However, it is difficult to diversify and improve the traditional four-axis robotic arm system due to the high software and hardware coupling and the single system design, which results in high production costs. At the same time, its low intelligence and high-power consumption limit its wide application. The paper proposes an embedded design of a four-axis manipulator system based on vision guidance. Based on the robot kinematics theory and geometric principles, the dynamics simulation of the manipulator model is carried out. Through the forward and reverse analysis of the manipulator model and the trajectory planning of the manipulator, the YOLOV7 target detection algorithm is introduced and deployed on the embedded device, which greatly reduces the manufacturing cost of the manipulator while meeting the control and power consumption requirements. It has been verified by experiments that the robot arm in this paper can achieve an end accuracy of 0.05 mm under the condition of a load of 1 kg using the ISO 9283 international standard, and the recognition algorithm adopted can achieve a recognition accuracy of 95.2% at a frame rate of 29. The overall power consumption is also lower than that of traditional robotic arms.