Multi-target objects and complex color recognition model based on humanoid robot

This research mainly focuses on the humanoid robot's recognition model for the multiple targets and complex color. The purpose of this research is to apply visual detection technology on a humanoid robot and propose a real time image extraction method to enhance the robot's visual application like a human. The multi-target objects and complex color experiments for various geometric shapes were conducted using humanoid robot NAO. The main procedure of the humanoid robot performing the operation of the multiple targets and complex color is as follows: firstly, the image is acquired by the vision system mounted on the camera of the humanoid robot; secondly, the pixel position of the object point is obtained through the image processing; furthermore, the outer shape position is set for the humanoid robot and then the improvement is performed to let it become more efficiencies. These experimental results demonstrate it can successfully identify the target objects and their outer contour, and also through the learning function in the Choregraphe platform, it can learn more complex definitions on the outer contour such as bottle and book and their recognition. The superiority of the proposed work is that it can be for various complex conditions. In the three-dimensional environment, the visual system of the NAO robot was firstly used to perceive its surrounding environment, and then the image processing technology was used to identify the chess position. The first general remark is that this work can be conceived as a good technological/engineering achievement.