RETRACTED: Design and implementation of badminton robot perception and control system

Abstract

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.

Retracted: Fast Recognition Method of Football Robot’s Graphics From the VR Perspective

“…In this experiment, the value of the radial basis function is 20. After completing the nonlinear Ostu training, all (H, S) T values will be traversed and solved by formula (7). If the result is greater than 0, it is marked as 1; if it is less than 0, it is marked as 0.…”

“…The omnidirectional vision system has perception and discrimination similar to human beings, and is the main recognition task in the vision system. Therefore, how to improve the rapid recognition ability of objects in the omnidirectional vision system from the perspective of robot virtual reality is the focus of this article [7,8].…”

Intelligent Badminton Training Robot in Athlete Injury Prevention Under Machine Learning

“…Mizuno et al (2019) developed a fully automatic badminton game robot, which could receive and serve in the same environment as the human athlete; the Kinect sensor and the space shuttle in this system were applied to predict and detect the motion trajectory of the shuttlecock. Liu et al (2020) collected depth images of the scene using a depth camera and applied the machine vision theory to process the obtained depth images. The position of the badminton camera coordinate system in the three-dimensional space was obtained by combining the image depth information.…”

“…The position of the field coordinate system was thus realized. Finally, the position information of the shuttlecock in the multi-frame image was adopted to predict the drop point of the shuttlecock; then, the badminton robot quickly ran to the predetermined position to complete the hitting task (Liu et al, 2020).…”