In the exploration of robot vision systems based on artificial neural networks, the research mainly focuses on their applications in 3D information recognition and processing. By simulating the processing of the human visual system, this technology enables robots to more effectively interpret and understand the three-dimensional spatial information of their environment, which has a revolutionary role in robot navigation, object recognition, obstacle avoidance and the execution of complex tasks. And this technology shows great potential in many fields such as industrial automation, autonomous vehicles, drone monitoring, and service robots. Not only that, it also plays a very important role in providing in-depth information, accurate positioning and efficient decision-making applications. According to the experimental data, among the 800 experimental subjects, more than 754 people were satisfied with the recognition accuracy, recognition speed, machine efficiency improvement, image recognition clarity, and overall satisfaction with the system. These findings indicate that with the continuous advancement of technology, 3D vision systems based on artificial neural networks will show more significant performance and value in future applications.