With the rapid development of computer technology, target tracking has become an indispensable technology in the field of image processing. Outline-based matching algorithms are one of the most representative methods in the field of computer vision. The idea is to extract several characteristic vectors from the image and compares them with the characteristic vectors in the corresponding image template. The difference between the image and the template characteristic vector is calculated, and the category is determined by the minimum distance method. The badminton robot collects the depth image of the scene through the depth camera and then uses the machine vision theory to process the acquired depth image. To combine the image depth information to obtain the position of the badminton camera coordinate system in the three-dimensional space, the position of the site coordinate system is achieved. Finally, the position information of the badminton in the multi-frame images is used to predict the falling point of the badminton. The badminton positioning and the analysis of the falling point are completed. The badminton robot quickly runs to the predicted position of the badminton and completes a hitting task. To realize the high-speed continuous and smooth badminton action of the badminton robot manipulator, a new multi-objective manipulator trajectory optimization model is proposed. The experimental results show that the new trajectory optimization model can effectively reduce the energy consumption of the motor and improve the rotational efficiency, thus ensuring the response speed of the arm.

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