 This research combines robotic arm control, computer vision, and deep learning technology to create an automated control system. It uses a YOLOV for algorithm to recognize user hand gestures, which are then sent to the robot arm control module via a communication module. This module analyzes the gesture commands and executes them accordingly. Engineers can use hand gestures to instruct the robot arm to record trajectories or execute specific tasks, making it easier to operate in real-world environments. This article was authored by Shang Liang Qin and Li Wu Huang.