The visual organ is important for animals to obtain information and understand the outside world; however, robots cannot do so without a visual system. At present, the vision technology of artificial intelligence has achieved automation and relatively simple intelligence; however, bionic vision equipment is not as dexterous and intelligent as the human eye. At present, robots can function as smartly as human beings; however, existing reviews of robot bionic vision are still limited. Robot bionic vision has been explored in view of humans and animals’ visual principles and motion characteristics. In this study, the development history of robot bionic vision equipment and related technologies are discussed, the most representative binocular bionic and multi-eye compound eye bionic vision technologies are selected, and the existing technologies are reviewed; their prospects are discussed from the perspective of visual bionic control. This comprehensive study will serve as the most up-to-date source of information regarding developments in the field of robot bionic vision technology.

This paper describes a novel bionic eye binocular vision system designed to mimic the natural movements of the human eye. The system provides a broader field of view and enhances visual perception in complex environments. Compared with similar bionic binocular cameras, the JEWXON BC200 bionic binocular camera developed in this study is more miniature. It consumes only 2.8 W of power, which makes it ideal for mobile robots. Combining axis and camera rotation enables more seamless panoramic image synthesis and is therefore suitable for self-rotating bionic binocular cameras. In addition, combined with the YOLO-V8 model, the camera can accurately recognize objects such as clocks and keyboards. This research provides new ideas for the development of robotic vision systems.

This paper mainly studies the structure and system of robot bionic eye. Given that most robots usually run on battery power, the STM32L053C8T6 with high efficiency and super low power consumption was selected as the main control. By carrying IMU, the bionic eye attitude data can be acquired quickly and accurately, and the measurement data of accelerometer and gyroscope can be fused by the algorithm to obtain stable and accurate bionic eye attitude data. Thus, the precise control of the motor can be realized through the drive control system equipped with PCA9685, which can enhance the motion control precision of robot bionic eye. In the present study, three kinds of IMU sensors, MPU6050, MPU9250, and WT9011G4K, were selected to carry out experiments. Finally, MPU9250 with better power consumption and adaptability is selected. This is the attitude acquisition device of bionic eye. In addition, three different filters, CF, GD, and EKF, were used for data fusion and comparison. The experimental result showed that the dynamic mean errors of CF, GD, and EKF are 0.62°, 0.61°, and 0.43°, respectively, and the static mean errors are 0.1017°, 0.1001°, and 0.0462°, respectively. The result showed that, after the use of EKF, the robot bionic eye system designed in this paper can significantly reduce the attitude angle error and effectively improve the image quality. It ensures accuracy and reduces power consumption and cost, which has lower requirements on hardware and is easier to popularize.