scholarly journals Badminton Path Tracking Algorithm Based on Computer Vision and Ball Speed Analysis

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yi Lyu ◽  
Shumin Zhang
Keyword(s):  
Computer Vision ◽  
Rotation Angle ◽  
Rapid Development ◽  
Path Tracking ◽  
Tracking Algorithm ◽  
Ball Speed ◽  
Position Information ◽  
Dynamic Tracking ◽  
Significant Difference ◽  
Path Tracking Algorithm

With the development of artificial intelligence and the rapid development of the computer industry, the practicability of computer vision programs is gradually improved. In this paper, the badminton path tracking algorithm based on computer vision analyzes the badminton trajectory and speed. This paper is aimed at analyzing the image processing technology and path tracking algorithm by using computer vision to obtain relevant data and then exploring the factors of badminton path and ball speed transformation, which provides reference significance for badminton players in future training. The path tracking algorithm is used to predict the rotation angle, the ball speed, and the athlete’s body information during the badminton movement through sensors, and the position information of the moving target is captured based on the visual field tracking and target dynamic tracking. Combined with specific badminton players, we first analyze the angle of each limb and the speed of the racket in the process of movement and record the data. Determine different positioning points for different actions, such as pushing the ball, picking the ball, hooking the ball, and rubbing the hair. In this process, we aim at the connection between the highest point and the lowest point of the badminton trajectory and the ball speed. This process fully combines the theoretical knowledge of the path tracking algorithm. The experimental results show that different service skills have different effects on the trajectory and speed of badminton. In the test of relevant data by using the push and receive skills, the lowest point of the ball served by player A in the first three times is higher than that by player B. The most significant difference between the lowest points of the five times is the second time, with a difference of 0.2 m, and the third time, with a minimum difference of 0.03 m.

scholarly journals INTELLIGENT CONTROL TECHNOLOGY OF AGRICULTURAL GREENHOUSE OPERATION ROBOT BASED ON FUZZY PID PATH TRACKING ALGORITHM

2020 ◽  
pp. 181-190
Author(s):  
Ren Qun
Keyword(s):  
Control System ◽  
Pid Control ◽  
Fuzzy Controller ◽  
Good Control ◽  
Path Tracking ◽  
Tracking Algorithm ◽  
Practical Significance ◽  
Fuzzy Pid ◽  
Path Tracking Algorithm

With the development of agricultural automation, applying intelligent algorithms to the navigation control of agricultural work vehicles has important practical significance for improving vehicle navigation accuracy and operation efficiency. In view of the complexity of the agricultural greenhouse environment, this study proposed a fuzzy PID path tracking algorithm based on the traditional vehicle PID control system. This algorithm uses a fuzzy controller to improve the PID control system, thereby realizing the online setting of PID control parameters. In order to verify the effectiveness of the fuzzy PID path tracking algorithm, the improved control system was applied to the tracked vehicle robot of Beijing Forestry University, and the operation performance of the vehicle robot was tested. The research results show that the absolute error rate of vehicle robot distance measurement is less than 1%; the error of the man-machine follow-up test is between 4 and 7 cm, and the measured follow-up distance is slightly less than the safe follow-up distance; the maximum error of the vehicle's fixed-point parking is 0.3 cm; The linear position tracking control has a lateral position deviation of ±3cm, and the vehicle's linear driving control and steering effects are better. The fuzzy PID path tracking algorithm designed this time shows good control performance, which has reference significance for the practical application of agricultural robots.

scholarly journals A Robust Numerical Path Tracking Algorithm for Polynomial Homotopy Continuation

2020 ◽  
Vol 42 (6) ◽  
pp. A3610-A3637
Author(s):  
Simon Telen ◽  
Marc Van Barel ◽  
Jan Verschelde
Keyword(s):  
Path Tracking ◽  
Tracking Algorithm ◽  
Homotopy Continuation ◽  
Path Tracking Algorithm

scholarly journals Target Tracking Algorithm for Table Tennis Using Machine Vision

2021 ◽  
Vol 2021 ◽  
pp. 1-7
Author(s):  
Hongtu Zhao ◽  
Fu Hao
Keyword(s):  
Neural Network ◽  
Machine Vision ◽  
Deep Neural Network ◽  
Tracking Algorithm ◽  
Tennis Ball ◽  
Table Tennis ◽  
Ball Speed ◽  
Position Information ◽  
Offline Learning ◽  
Hidden Layer

The current table tennis robot system has two common problems. One is the table tennis ball speed, which moves fast, and it is difficult for the robot to react in a short time. The second is that the robot cannot recognize the type of the ball's movement, i.e., rotation, top rotation, no rotation, wait, etc. It is impossible to judge whether the ball is rotating and the direction of rotation, resulting in a single return strategy of the robot with poor adaptability. In this paper, these problems are solved by proposing a target trajectory tracking algorithm for table tennis using machine vision combined with Scaled Conjugate Gradient (SCG). Real human-machine game’s data are obtained in the proposed algorithm by extracting ten continuous position information and speed information frames for feature selection. These features are used as input data for the deep neural network and then are normalized to create a deep neural network algorithm model. The model is trained by the position information of the successive 20 frames. During the initial sets of experiments, we found the shortcomings of the original SCG algorithm. By setting the accuracy threshold and offline learning of historical data and saving the hidden layer weight matrix, the SCG algorithm was improved. Finally, experiments verify the improved algorithm's feasibility and applicability and show that the proposed algorithm is more suitable for table tennis robots.

Parameter Self-Adjusting Path Tracking Algorithm of Mobile Robots

2013 ◽  
Vol 418 ◽  
pp. 10-14 ◽  
Author(s):  
Hong Ji Zhang ◽  
Yuan Yuan Ge
Keyword(s):  
Tracking Control ◽  
Control Algorithm ◽  
Control Object ◽  
Learning Objects ◽  
Path Tracking ◽  
Tracking Algorithm ◽  
Tracking Accuracy ◽  
Path Tracking Algorithm ◽  
Robot Path

For conventional fuzzy path tracking controller need to manually updated the control parameters in order to get better tracking control deficiencies and the lack of robustness of the problem when the control object is disturbed. Parameters self-adjusting tracking algorithm is proposed based on Cerebellum Model Articulation Controller(CMAC) and fuzzy logic composite of the control. The CAMC control logarithm first charged with tracking through learning objects charged with approximation of the object model, to learning cycle worth to control corresponding to the amount of correction corresponding weight value according to the error between input and output of the system and set the learning rate. When the object or environment changes can make the control performance of the system is automatically adjusting within a certain range, since the role of the CAMC. Tracking experiments show that. The tracking control algorithm has high tracking accuracy and good robustness, is conducive to the overall optimization of robot path tracking.

scholarly journals A Path Tracking Method for Autonomous Rice Drill Seeder in Paddy Fields

2018 ◽  
Vol 220 ◽  
pp. 04004
Author(s):  
Yan Zhang ◽  
Yanming Li ◽  
Yixiang Huang ◽  
Xiangpeng Liu ◽  
Chengliang Liu
Keyword(s):  
Control Model ◽  
Path Tracking ◽  
Tracking Algorithm ◽  
Paddy Fields ◽  
Steering Control ◽  
Lateral Deviation ◽  
Angle Deviation ◽  
Heading Angle ◽  
The Mean ◽  
Path Tracking Algorithm

For the purpose of overcoming the obstacles in application of autonomous rice drill seeder in paddy fields, a path tracking algorithm with high accuracy used for steering control during straight traveling in uneven muddy paddy fields is introduced in this paper. Combining lateral deviation and heading angle deviation as feedback, a nonlinear steering control model is developed in the algorithm. To avoid the position error caused by incline, the influence brought by the roll angle and the pitch angle of the vehicle on position coordinates are taken into account when the vehicle is on a slant. The experiments carried out in arable paddy fields show that the mean absolute lateral deviation of the algorithm was less than 2.9 centimeters and the heading angle deviation was less than 0.03°. The path tracking algorithm is able to meet the required precision for autonomous rice drill seeder in paddy fields of China.

Sign in / Sign up

Export Citation Format

Share Document