Real time evaluation algorithm of human motion in tennis training robot

2020 ◽  
pp. 1-9
Author(s):  
Yingying Wang ◽  
Yongzhi Zhang
Keyword(s):  
Real Time ◽  
Rapid Development ◽  
Human Movement ◽  
Human Motion ◽  
Sports Activity ◽  
Training Requirements ◽  
Core Theory ◽  
Evaluation Algorithm ◽  
Stability And Accuracy ◽  
Time Evaluation

Tennis is a set of sports and entertainment and a sports activity, since 2014, tennis in China has been another rapid development. With the development of economy and technology, tennis training mode has been further optimized and reformed. At present, tennis training robot is the mainstream way to train athletes. However, there are some defects in the current tennis training robots, such as the low accuracy of human motion real-time evaluation, and the lack of stability. Therefore, this paper puts forward the related research on the real-time evaluation algorithm of human motion in tennis training robots, hoping to make up for the deficiency in this field. The research of this paper is mainly divided into four parts. The first part is to analyze the current situation of technology research in this field and put forward the idea of this paper by analyzing the shortcomings of the existing technology. The second part is the related basic theory research; this part deeply studies the core theory of tennis training and intelligent training robot, which provides a theoretical basis for the realization of the optimization scheme. The third part is the design and implementation of a real-time human motion evaluation optimization algorithm for tennis training robots. At the end of the paper, that is, the fourth part, through the way of field test and investigation, further proves the superiority of the improved real-time evaluation algorithm of human movement. The algorithm has good stability and accuracy and can meet the existing tennis training requirements.

scholarly journals Real-Time Evaluation Algorithm of Human Body Movement in Football Training Robot

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Ning Hu ◽  
Shuhua Lin ◽  
Jiayi Cai
Keyword(s):  
Artificial Intelligence ◽  
Real Time ◽  
Vision System ◽  
Body Movement ◽  
Human Motion ◽  
Wide Range ◽  
Evaluation Algorithm ◽  
Football Training ◽  
Time Evaluation ◽  
Soccer Robots

As one of the most challenging topics in the field of artificial intelligence, soccer robots are currently an important platform for humanoid robotics research. Its fields cover a wide range of fields, including robotics, artificial intelligence, and automatic control. Kinematics analysis and action planning are the key technologies in the research of humanoid soccer robots and are the basis for realizing basic actions such as walking. This article mainly introduces the real-time evaluation algorithm of human motion in the football training robot. The football robot action evaluation algorithm proposed here designs the angle and wheel speed of the football robot movement through the evaluation of the angular velocity and linear velocity of the center of mass of the robot. The overall system of the imitation human football robot is studied, including the mechanical system design. The design of the leg structure, the decision-making system based on the finite state machine, the robot vision system, and the image segmentation technology are introduced. The experimental results in this article show that the action of the football training robot model is very stable, the static rotation movement time is about 220 ms, and the fixed-point movement error is less than 1 cm, which fully meets the accuracy requirements of the large-space football robot.

scholarly journals A Flexible and Stretchable Self-Powered Nanogenerator in Basketball Passing Technology Monitoring

Electronics ◽  
2021 ◽  
Vol 10 (21) ◽  
pp. 2584
Author(s):  
Changjun Jia ◽  
Yongsheng Zhu ◽  
Fengxin Sun ◽  
Tianming Zhao ◽  
Rongda Xing ◽  
...  
Keyword(s):  
Real Time ◽  
Inorganic Salt ◽  
Rapid Development ◽  
Human Motion ◽  
Small Scale ◽  
New Approach ◽  
Motion Data ◽  
Fifth Generation ◽  
Self Powered ◽  
Generation Technology

The rapid development of the fifth generation technology poses more challenges in the human motion inspection field. In this study, a nanogenerator, made by PVDF, ionic hydrogel, and PDMS, is used. Furthermore, a transparent, stretchable, and biocompatible PENG (TSB-PENG) is presented, which can be used as a self-powered sensor attached to the athlete’s joints, which helps to monitor the training and improve the subject’s performance. This device shows the ability to maintain a relatively stable output, under various external environments (e.g., inorganic salt, organic matter and temperature). Additionally, TSB-PENG can supply power to small-scale electronic equipment, such as Bluetooth transmitting motion data in real time. This study can provide a new approach to designing lossless, real-time, portable, and durable self-powered sensors in the sports motoring field.

The Research of 3D Human Motion Simulation and Video Analysis System Implemented in Sports Training

2014 ◽  
Vol 926-930 ◽  
pp. 2743-2746 ◽  
Author(s):  
Rui Min Hu ◽  
Zhen Dong He ◽  
Feng Bai
Keyword(s):  
Computer Vision ◽  
Video Analysis ◽  
Rapid Development ◽  
Human Movement ◽  
Research Direction ◽  
Human Motion ◽  
Motion Simulation ◽  
Sports Training ◽  
Camera Tracking ◽  
Human Motion Simulation

With the rapid development of computer technology, human motion tracking based on video is a kind of using ordinary camera tracking unmarked human movement technology. It has important application value in automatic monitoring, human-computer interaction, sports analysis and many other fields. This research is a hot research direction in the field of computer vision in recent years. Because of the complexity of the problem and the lack of understanding of the nature of the human visual tracking based on video is always a difficult problem in computer vision. The research content of this article is set in sports training, for motion analysis of non-contact, no interfere with measurement and simulation requirements, the use of computer graphics and computer vision technology, discussing 3D human motion simulation technology based on video analysis.

scholarly journals TO THE PROBLEM OF APPLYING WI-FI ACCESS POINTS FOR REGISTERING MOTION AT THE SITE IN THE ABSENCE OF A WI-FI MODULE

2019 ◽  
pp. 73-78 ◽  
Author(s):  
Ivan Leonidovich Reva ◽  
Alexey Aleksandrovich Bogdanov ◽  
Ekaterina Andreevna Malakhova
Keyword(s):  
Global Positioning System ◽  
Rapid Development ◽  
Human Movement ◽  
Human Motion ◽  
Radio Network ◽  
New Approach ◽  
Unauthorized Access ◽  
Single Person ◽  
Global Positioning ◽  
Access Control System

The article describes the problem of registration of human movement on the object and protection of the object against unauthorized access. Global Positioning System which is well proven in open field has low precision within the premises. Due to the rapid development of Wi-Fi technology and the need to organize monitoring of human motion in the protected premises, there is being developed a new approach to registering a person on site using Wi-Fi. The problem of registering unauthorized access to the object by means of Wi-Fi radio network has been considered, its strengths and weaknesses have been studied. Most organizations actively use corporative and public Wi-Fi networks and beneficially apply this well-developed infrastructure for detecting the human presence in the premises and determining their position. It has been stated that using Wi-Fi network is more profitable than installing a special access control system. The aim of the research is to develop a human motion registering system at the site protected without using a Wi-Fi-module. There have been presented experiment results of registering human motion by means of the well-developed Wi-Fi infrastructure, the experiments being conducted to analyze changes of a signal level at different positions of a single person or a number of persons in the premises. It has been inferred that the level of Wi-Fi signal changes when a person or a group of persons are present in the room, even if they don’t have a Wi-Fi-module; this fact helps register the human motion in the protected premises.

scholarly journals A REAL-TIME PHOTOGRAMMETRIC SYSTEM FOR MONITORING HUMAN MOVEMENT DYNAMICS

2020 ◽  
Vol XLIII-B2-2020 ◽  
pp. 561-566
Author(s):  
L. Chen ◽  
B. Wu ◽  
Y. Zhao
Keyword(s):  
Real Time ◽  
Human Body ◽  
Large Scale ◽  
Human Movement ◽  
Human Motion ◽  
Body Posture ◽  
Efficient Estimation ◽  
Process Unit ◽  
Movement Dynamics ◽  
Body Dynamics

Abstract. The human body posture is rich with dynamic information that can be captured by algorithms, and many applications rely on this type of data (e.g., action recognition, people re-identification, human-computer interaction, industrial robotics). The recent development of smart cameras and affordable red-green-blue-depth (RGB-D) sensors has enabled cost-efficient estimation and tracking of human body posture. However, the reliability of single sensors is often insufficient due to occlusion problems, field-of-view limitations, and the limited measurement distances of the RGB-depth sensors. Furthermore, a large-scale real-time response is often required in certain applications, such as physical rehabilitation, where human actions must be detected and monitored over time, or in industries where human motion is monitored to maintain predictable movement flow in a shared workspace. Large-scale markerless motion-capture systems have therefore received extensive research attention in recent years.In this paper, we propose a real-time photogrammetric system that incorporates multithreading and a graphic process unit (GPU)-accelerated solution for extracting 3D human body dynamics in real-time. The system includes a stereo camera with preliminary calibration, from which left-view and right-view frames are loaded. Then, a dense image-matching algorithm is married with GPU acceleration to generate a real-time disparity map, which is further extended to a 3D map array obtained by photogrammetric processing based on the camera orientation parameters. The 3D body features are acquired from 2D body skeletons extracted from regional multi-person pose estimation (RMPE) and the corresponding 3D coordinates of each joint in the 3D map array. These 3D body features are then extracted and visualised in real-time by multithreading, from which human movement dynamics (e.g., moving speed, knee pressure angle) are derived. The results reveal that the process rate (pose frame-rate) can be 20 fps (frames per second) or above in our experiments (using two NVIDIA 2080Ti and two 12-core CPUs) depending on the GPU exploited by the detector, and the monitoring distance can reach 15 m with a geometric accuracy better than 1% of the distance.This real-time photogrammetric system is an effective real-time solution to monitor 3D human body dynamics. It uses low-cost RGB stereo cameras controlled by consumer GPU-enabled computers, and no other specialised hardware is required. This system has great potential for applications such as motion tracking, 3D body information extraction and human dynamics monitoring.

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