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AR Marker Detection Technique-Based Autonomous Attitude Control for a nonGPS Aided Quadcopter

Korean Journal of Artificial Intelligence / Korean Journal of Artificial Intelligence, (E)2508-7894
2024, v.12 no.3, pp.9-15
https://doi.org/10.24225/kjai.2024.12.3.9
Yeonwoo LEE (Mokpo National University)
KANG Sun-Kyung (Wonkwang University)
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Abstract

This paper addresses the critical need for quadcopters in GPS-denied indoor environments by proposing a novel attitude control mechanism that enables autonomous navigation without external guidance. Utilizing AR marker detection integrated with a dual PID controller algorithm, this system ensures accurate maneuvering and positioning of the quadcopter by compensating for the absence of GPS, a common limitation in indoor settings. This capability is paramount in environments where traditional navigation aids are ineffective, necessitating the use of quadcopters equipped with advanced sensors and control systems. The actual position and location of the quadcopter is achieved by AR marker detection technique with the image processing system. Moreover, in order to enhance the reliability of the attitude PID control, the dual closed loop control feedback PID control with dual update periods is suggested. With AR marker detection technique and autonomous attitude control, the proposed quadcopter system decreases the need of additional sensor and manual manipulation. The experimental results are demonstrated that the quadrotor’s autonomous attitude control and operation with the dual closed loop control feedback PID controller with hierarchical (inner-loop and outer-loop) command update period is successfully performed under the non-GPS aided indoor environment and it enhanced the reliability of the attitude and the position PID controllers within 17 seconds. Therefore, it is concluded that the proposed attitude control mechanism is very suitable to GPS-denied indoor environments, which enables a quadcopter to autonomously navigate and hover without external guidance or control.

keywords
AR marker, Attitude control algorithm, Image processing, GPS, Quadcopter
Submission Date
2024-06-02
Revised Date
2024-07-17
Accepted Date
2024-09-05

Korean Journal of Artificial Intelligence