An interactive ball training partner robot based on YOLOv5
In order to solve the problem of insufficient human-computer interaction ability of ball training partner robots, a new human-computer interaction mode based on Raspberry Pi and YOLOv5 algorithm was proposed, which enabled the robot to realize six different actions: forward, backward, left, right, t...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | zho |
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National Computer System Engineering Research Institute of China
2022-01-01
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| Series: | Dianzi Jishu Yingyong |
| Subjects: | |
| Online Access: | http://www.chinaaet.com/article/3000145083 |
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| _version_ | 1849421573644091392 |
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| author | Zeng Yangji Liu Zihong Cai Yong Guo Xingchen Mo Jinlong |
| author_facet | Zeng Yangji Liu Zihong Cai Yong Guo Xingchen Mo Jinlong |
| author_sort | Zeng Yangji |
| collection | DOAJ |
| description | In order to solve the problem of insufficient human-computer interaction ability of ball training partner robots, a new human-computer interaction mode based on Raspberry Pi and YOLOv5 algorithm was proposed, which enabled the robot to realize six different actions: forward, backward, left, right, throwing the ball, and kicking the ball. After calibrating and training the data sets collected in three different environments(indoor, outdoor sunny day and outdoor cloudy day), the recognition accuracy of the six poses in the test set under three different environments is 96.33% indoor，95% outdoor sunny day，and 94.3% outdoor cloudy day, respectively. Compared with other algorithms based on feature matching and small target detection using gestures, the robot has higher detection speed and accuracy, which makes the robot more intelligent. |
| format | Article |
| id | doaj-art-0903d374ce8b4582804b825d45fb38e3 |
| institution | Kabale University |
| issn | 0258-7998 |
| language | zho |
| publishDate | 2022-01-01 |
| publisher | National Computer System Engineering Research Institute of China |
| record_format | Article |
| series | Dianzi Jishu Yingyong |
| spelling | doaj-art-0903d374ce8b4582804b825d45fb38e32025-08-20T03:31:25ZzhoNational Computer System Engineering Research Institute of ChinaDianzi Jishu Yingyong0258-79982022-01-01481767910.16157/j.issn.0258-7998.2117363000145083An interactive ball training partner robot based on YOLOv5Zeng Yangji0Liu Zihong1Cai Yong2Guo Xingchen3Mo Jinlong4School of Manufacturing Science and Engineering，Southwest University of Science and Technology，Mianyang 621000，ChinaSchool of Manufacturing Science and Engineering，Southwest University of Science and Technology，Mianyang 621000，ChinaSchool of Manufacturing Science and Engineering，Southwest University of Science and Technology，Mianyang 621000，ChinaSchool of Manufacturing Science and Engineering，Southwest University of Science and Technology，Mianyang 621000，ChinaSchool of Manufacturing Science and Engineering，Southwest University of Science and Technology，Mianyang 621000，ChinaIn order to solve the problem of insufficient human-computer interaction ability of ball training partner robots, a new human-computer interaction mode based on Raspberry Pi and YOLOv5 algorithm was proposed, which enabled the robot to realize six different actions: forward, backward, left, right, throwing the ball, and kicking the ball. After calibrating and training the data sets collected in three different environments(indoor, outdoor sunny day and outdoor cloudy day), the recognition accuracy of the six poses in the test set under three different environments is 96.33% indoor，95% outdoor sunny day，and 94.3% outdoor cloudy day, respectively. Compared with other algorithms based on feature matching and small target detection using gestures, the robot has higher detection speed and accuracy, which makes the robot more intelligent.http://www.chinaaet.com/article/3000145083yolov5 algorithmposture recognitionball training partner robotraspberry pistm32 mcu |
| spellingShingle | Zeng Yangji Liu Zihong Cai Yong Guo Xingchen Mo Jinlong An interactive ball training partner robot based on YOLOv5 Dianzi Jishu Yingyong yolov5 algorithm posture recognition ball training partner robot raspberry pi stm32 mcu |
| title | An interactive ball training partner robot based on YOLOv5 |
| title_full | An interactive ball training partner robot based on YOLOv5 |
| title_fullStr | An interactive ball training partner robot based on YOLOv5 |
| title_full_unstemmed | An interactive ball training partner robot based on YOLOv5 |
| title_short | An interactive ball training partner robot based on YOLOv5 |
| title_sort | interactive ball training partner robot based on yolov5 |
| topic | yolov5 algorithm posture recognition ball training partner robot raspberry pi stm32 mcu |
| url | http://www.chinaaet.com/article/3000145083 |
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