Autonomous shuttlecock collecting robot

Badminton is one of the favorite sports among the society in this century. The badminton players range from male to female and youths to elderlies. Due to its popularity, a lot of badminton equipment are invented to increase the efficiency of the training. Besides the basic equipment such as racquet...

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Main Author: Chew, Min Jian
Other Authors: Heng Kok Hui, John Gerard
Format: Final Year Project
Language:English
Published: Nanyang Technological University 2021
Subjects:
Online Access:https://hdl.handle.net/10356/150420
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1504202021-05-28T01:58:20Z Autonomous shuttlecock collecting robot Chew, Min Jian Heng Kok Hui, John Gerard School of Mechanical and Aerospace Engineering mkhheng@ntu.edu.sg Engineering::Mechanical engineering::Robots Engineering::Mechanical engineering::Mechatronics Badminton is one of the favorite sports among the society in this century. The badminton players range from male to female and youths to elderlies. Due to its popularity, a lot of badminton equipment are invented to increase the efficiency of the training. Besides the basic equipment such as racquet and shuttlecock, there are also badminton equipment such as badminton equipment bag, badminton headband, wrist band, badminton shoes, badminton shorts and shuttlecock launcher available in the market. Shuttlecock launcher is popular for badminton training, however there is nothing available to collect the shuttlecocks currently. Therefore, the purpose of this project is to design and develop an autonomous shuttlecock collecting robot. With this robot, the training efficiency of the badminton players can be increased significantly as the players can concentrate of their training since the shuttlecock collecting task can be done by the robot. The report will discuss on the software system of the robot which focus on the shuttlecock detection by deep learning model, optimization of the deep learning model in order to implement on microcontroller and the navigation system of the robot. In this project, SSD model trained by TensorFlow is able to achieve an inference speed of 15fps when performing shuttlecock recognition on a laptop without GPU. The SSD model is then optimised by Intel OpenVino and result in a significant increase of inference speed (max 35fps) during the shuttlecock recognition on a resources constraint microcontroller, Raspberry Pi 4 Model B. At the end of the project, an autonomous shuttlecock collecting robot is successfully developed and it is able to detect shuttlecocks by camera and navigate to the location of the shuttlecocks for collecting purpose. Bachelor of Engineering (Mechanical Engineering) 2021-05-28T01:58:20Z 2021-05-28T01:58:20Z 2021 Final Year Project (FYP) Chew, M. J. (2021). Autonomous shuttlecock collecting robot. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/150420 https://hdl.handle.net/10356/150420 en A251 application/pdf Nanyang Technological University
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic Engineering::Mechanical engineering::Robots
Engineering::Mechanical engineering::Mechatronics
spellingShingle Engineering::Mechanical engineering::Robots
Engineering::Mechanical engineering::Mechatronics
Chew, Min Jian
Autonomous shuttlecock collecting robot
description Badminton is one of the favorite sports among the society in this century. The badminton players range from male to female and youths to elderlies. Due to its popularity, a lot of badminton equipment are invented to increase the efficiency of the training. Besides the basic equipment such as racquet and shuttlecock, there are also badminton equipment such as badminton equipment bag, badminton headband, wrist band, badminton shoes, badminton shorts and shuttlecock launcher available in the market. Shuttlecock launcher is popular for badminton training, however there is nothing available to collect the shuttlecocks currently. Therefore, the purpose of this project is to design and develop an autonomous shuttlecock collecting robot. With this robot, the training efficiency of the badminton players can be increased significantly as the players can concentrate of their training since the shuttlecock collecting task can be done by the robot. The report will discuss on the software system of the robot which focus on the shuttlecock detection by deep learning model, optimization of the deep learning model in order to implement on microcontroller and the navigation system of the robot. In this project, SSD model trained by TensorFlow is able to achieve an inference speed of 15fps when performing shuttlecock recognition on a laptop without GPU. The SSD model is then optimised by Intel OpenVino and result in a significant increase of inference speed (max 35fps) during the shuttlecock recognition on a resources constraint microcontroller, Raspberry Pi 4 Model B. At the end of the project, an autonomous shuttlecock collecting robot is successfully developed and it is able to detect shuttlecocks by camera and navigate to the location of the shuttlecocks for collecting purpose.
author2 Heng Kok Hui, John Gerard
author_facet Heng Kok Hui, John Gerard
Chew, Min Jian
format Final Year Project
author Chew, Min Jian
author_sort Chew, Min Jian
title Autonomous shuttlecock collecting robot
title_short Autonomous shuttlecock collecting robot
title_full Autonomous shuttlecock collecting robot
title_fullStr Autonomous shuttlecock collecting robot
title_full_unstemmed Autonomous shuttlecock collecting robot
title_sort autonomous shuttlecock collecting robot
publisher Nanyang Technological University
publishDate 2021
url https://hdl.handle.net/10356/150420
_version_ 1701270558835998720