Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/150420
Title: Autonomous shuttlecock collecting robot
Authors: Chew, Min Jian
Keywords: Engineering::Mechanical engineering::Robots
Engineering::Mechanical engineering::Mechatronics
Issue Date: 2021
Publisher: Nanyang Technological University
Source: Chew, M. J. (2021). Autonomous shuttlecock collecting robot. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/150420
Project: A251
Abstract: 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.
URI: https://hdl.handle.net/10356/150420
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:MAE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
FYP Report Final_ChewMinJian.pdf
  Restricted Access
4.18 MBAdobe PDFView/Open

Page view(s)

146
Updated on May 17, 2022

Download(s)

21
Updated on May 17, 2022

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.