Implementation of intelligent robot target recognition technology based on FPGA development platform

Deep learning is currently a popular development in the field of artificial intelligence, which is based on the analysis of the process of input and processing information by the human brain, and the encoding and implementation of that process by a computer. There has been a tremendous development in deep learning for image and speech recognition, resulting in a number of related application technologies. FPGAs (Field Programmable Logic Gate Arrays), as a semi-custom, reconfigurable hardware device, are increasingly used in the field of artificial intelligence. Intelligent robots, which combine information processing capabilities such as image, text, speech, position and motion, have very promising applications in industrial production and social life. In this paper, the correctness of the functionality of each functional module is confirmed through simulation, on-board verification schemes are designed and data results are statistically and analytically analysed, demonstrating the stability of the circuit system. The FPGA implementation based on the YOLOv3 algorithm was confirmed to be highly usable by connecting the development platform to an intelligent robot and conducting a comparative analysis.