Quadcopter Position Hold Function using Optical Flow in a Smartphone-based Flight Computer

  • Noel P. Caliston Iloilo State University of Fisheries Science and Technology, Philippines
  • Chris Jordan G. Aliac College of Computer Studies, Cebu Institute of Technology University, Philippines
  • James Arnold E. Nogra College of Computer Studies, Cebu Institute of Technology University, Philippines

Abstract

Purpose – This paper explores the capability of smartphones as computing devices for a quadcopter, specifically in terms of the ability of drones to maintain a position known as the position hold function. Image processing can be performed with the phone's sensors and powerful built-in camera.

Method – Using Shi-Tomasi corner detection and the Lucas-Kanade sparse optical flow algorithms, ground features are recognized and tracked using the downward-facing camera. The position is maintained by computing quadcopter displacement from the center of the image using Euclidian distance, and the corresponding pitch and roll estimate is calculated using the PID controller.

Results – Actual flights show a double standard deviation of 18.66 cm from the center for outdoor tests. With a quadcopter size of 58cm x 58cm used, it implies that 95% of the time, the quadcopter is within a diameter of 96 cm. For indoor tests, a double standard deviation of 10.55 cm means that 95% of the time, the quadcopter is within a diameter of 79 cm.

Conclusion – Smartphone sensors and cameras can be used to perform optical flow position hold functions, proving their potential as computing devices for drones.

Recommendations – To further improve the positioning system of the phone-based quadcopter system, it is suggested that potential sensor fusion be explored with the phone's GNSS sensor, which gives absolute positioning information for outdoor applications.

Research Implications – As different devices and gadgets are integrated into the smartphone, this paper presents an opportunity for phone manufacturers and researchers to explore the potential of smartphones for a drone use-case.

Author Biographies

Noel P. Caliston, Iloilo State University of Fisheries Science and Technology, Philippines

Noel P. Caliston completed his Master in Information Technology at Cebu Institute of Technology University, Cebu City, Philippines, and is currently in the dissertation phase of the Doctor in Information Technology at the same university. He is also a faculty of the College of Information and Communication Technology at Iloilo State University of Fisheries Science and Technology – Dingle Campus, Dingle, Iloilo, Philippines. His teaching areas are computer programming and emerging technologies. His research interests are embedded systems, machine learning, and artificial intelligence.

Chris Jordan G. Aliac, College of Computer Studies, Cebu Institute of Technology University, Philippines

Chris Jordan G. Aliac finished his bachelor’s degree in Computer Engineering, master's in Computer Science, and doctorate in Information Technology at Cebu Institute of Technology University, Cebu City, Philippines. He is also a certified cloud practitioner by Amazon Web Service and a Certified Professional Computer Engineer by the Philippine Computer Engineering Certification Board. He focuses his research on artificial intelligence, specializing in Robotics and Machine Learning, Embedded and Distributed Systems, and ICT Security. He is also the CIT University’s Makespace manager and CIT University's ICT security Head. He is also a Full Professor at the College of Computer Studies at the same University.

James Arnold E. Nogra, College of Computer Studies, Cebu Institute of Technology University, Philippines

James Arnold E. Nogra is an experienced industry practitioner in mobile, web, and full-stack development. He finished his bachelor's degree in Computer Science at the University of the Philippines. He completed his master's in Computer Science and doctorate in Information Technology at Cebu Institute of Technology University, Cebu City, Philippines. He also teaches subjects related to computer programming and data mining. His research interests are in the field of neural networks.

Published
2024-05-15
How to Cite
CALISTON, Noel P.; ALIAC, Chris Jordan G.; NOGRA, James Arnold E.. Quadcopter Position Hold Function using Optical Flow in a Smartphone-based Flight Computer. International Journal of Computing Sciences Research, [S.l.], v. 8, p. 2809-2821, may 2024. ISSN 2546-115X. Available at: <//www.stepacademic.net/ijcsr/article/view/514>. Date accessed: 26 june 2024.
Section
Articles