Badminton motion capture with visual image detection of picking robotics

Abstract

In the process of strawberry easily broken fruit picking, in order to reduce the damage rate of the fruit, improves accuracy and efficiency of picking robot, field put forward a motion capture system based on international standard badminton edge feature detection and capture automation algorithm process of night picking robot badminton motion capture techniques training methods. The badminton motion capture system can analyze the game video in real time and obtain the accuracy rate of excellent badminton players and the technical characteristics of badminton motion capture through motion capture. The purpose of this article is to apply the high-precision motion capture vision control system to the design of the vision control system of the robot in the night picking process, so as to effectively improve the observation and recognition accuracy of the robot in the night picking process, so as to improve the degree of automation of the operation. This paper tests the reliability of the picking robot vision system. Taking the environment of picking at night as an example, image processing was performed on the edge features of the fruits picked by the picking robot. The results show that smooth and enhanced image processing can successfully extract edge features of fruit images. The accuracy of the target recognition rate and the positioning ability of the vision system of the picking robot were tested by the edge feature test. The results showed that the accuracy of the target recognition rate and the positioning ability of the motion edge of the vision system were far higher than 91%, satisfying the automation demand of the picking robot operation with high precision.

Application and Practice of Motion Capture Technology in Badminton Teaching

“…Through swinging movements, sprinting, and jumping, playing badminton can enhance muscle strength and endurance, thus further improving physical fitness [9][10]. Traditional badminton teaching focuses on improving the degree of technical mastery of the students, ignoring the important factor of subjective interest of the students and ignoring the sense of experience and fulfillment of the badminton students in the course [11][12]. Therefore, the traditional single badminton teaching has been unable to meet the actual needs of young people and must take scientific teaching methods for young people to learn badminton to create a relaxing and pleasant teaching environment.…”

A Dragon Fruit Picking Detection Method Based on YOLOv7 and PSP-Ellipse

“…Nowadays, dragon fruit is usually harvested manually by cutting its branch that is connected with the root, which causes a lot of labor intensity. Research is being conducted on the dragon fruit picking robot to realize automatic picking, which could greatly reduce the labor force [3,4]. Visual intelligence is of key importance to the fruit picking robot [5].…”