Real-time Ball Detection and Tracking using Raspberry PI

Authors

  • Dharma Aryani Politeknik Negeri Ujung Pandang
  • Kartika Dewi
  • Fery Ta.by
  • Evita Putri Sanggaria

DOI:

https://doi.org/10.31963/intek.v10i1.4301

Keywords:

Raspberry Pi, Open CV, Webcam, Ball Tracking.

Abstract

This paper presents a real-time system for ball detection and tracking system which is reliable in any conditions. Images from the webcam are processed by openCV library running on a Raspberry Pi to move the camera pan and tilt servo and two DC motors to drive the robot body using the Arduino Nano microcontroller.  The webcam is integrated in a robot prototype to represent the wheel football robot type. The results show that a ball tracking webcam system is obtained with the capability to detect a ball with a diameter of 17cm within a maximum distance of 200 cm, a stable ball reading when the light intensity is at 32 lux and above. Furthermore, the experimental results demonstrated the system’s robustness in detecting and tracking ball in different distance and ligthing conditions.

Author Biography

Dharma Aryani, Politeknik Negeri Ujung Pandang

Teknik Elektro

References

References

Jung, B., Sukhatme, G.S. Real-time Motion Tracking from a Mobile Robot. Int J of Soc Robotics 2, 63–78 (2010)

Peter Chondro, Shanq-Jang Ruan, “An adaptive background estimation for real-time obejct localization on a color-coded environment,†IEEE International Conference on Advanced Computer Science and Information (ICACSIS), pp. 464-469, Malang-Indonesia, October 2016.

Phua Seong Hock, S. Parasuraman, “Motion synchronization with predefined rhythms for humanoid robot,†IEEE-Recent Advances in Intelegent Computational Systems (RAICS), pp. 294-299, Trivandrum India, December 2015.

Susanto, Eko Rudiawan, Riska Analia, Sutopo Daniel, Hendawan Soebakti, “The deep learning development for real-time ball and goal detection of barelang-FC.†,IEEE 2017 International Electronics Symposium on Engineering Technology and Applications (IES-ETA) - Surabaya 2017

André Treptow, Andreas Zell, “Real-time object tracking for soccer-robots without color informationâ€, Robotics and Autonomous Systems,Volume 48, Issue 1, 2004

OpenCV Documentation, OpenCV - Open Computer Vision Library.

Muharom, S., Automatics detect and Shooter Robot based on object detection using camera. PrzeglÄ…d Elektrotechniczny, 2022.

Raspberry Pi. “Raspberry Pi 3 Model Bâ€, (https://www.raspberrypi.org/products/raspberry-pi-3-model-b/?resellerType=home, diakses 23 November 2020).

Downloads

Published

2023-04-01

Issue

Section

ARTICLES