Research on the Application of Deep Learning Algorithm in Visual Perception and Recognition of Artificial Intelligence Robot

With the rapid advancement of science and technology, artificial intelligence (AI) has emerged as a focal point in the realm of technology. Among its core branches, deep learning endows computers with formidable data processing capabilities by emulating the cognitive processes of the human brain. This work delves into the application of deep learning in robotic visual perception, encompassing areas such as image recognition, object detection, and motion planning, thereby illustrating how deep learning algorithms can markedly enhance a robot’s visual perception capabilities. To validate these enhancements, the YOLOv5 model was employed for real-time object detection, which was further integrated with the A* algorithm for robotic path planning. The outcomes demonstrate that the YOLOv5-based object detection algorithm performs admirably in complex environments. Collectively, this research furnishes fresh perspectives and methodologies for the progression of robotics technology in the future.