Leader - Follower based Formation Guidance Law and Autonomous Formation Flight Test of Multiple MAVs

You, Dong-Il; Shim, Hyunchul

doi:10.5139/jksas.2010.39.2.121

Cited by 5 publications

(2 citation statements)

References 3 publications

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“…The onboard video was taken from the UAV turning in the clockwise direction. [12] The first phase of the image processing algorithm for detecting and tracking of aerial vehicle in short range is to detect and track features from images of the ground. In Fig.…”

Section: Image Processing Resultsmentioning

confidence: 99%

An image processing algorithm for detection and tracking of aerial vehicles

Cho

Huh

Choi

et al. 2011

IEEE Conference on Decision and Control and European Control Conference

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This paper proposes an image processing algorithm for detection and tracking of aerial vehicles in sight. The proposed algorithm detects moving objects using the image homography calculated from a video stream taken from the onboard camera and determines whether the detected objects are approaching aerial vehicles by the Probabilistic Multi-Hypothesis Tracking (PMHT) method. This algorithm performs well especially when it is needed to detect any approaching aircraft seen with cluttered background. Further, our algorithm is suitable for real flight application as it is less sensitive to light conditions or color variations. The performance of the proposed algorithm is validated by applying it to the onboard video clips taken during actual flights using two unmanned aerial vehicles.

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Section: Image Processing Resultsmentioning

confidence: 99%

An image processing algorithm for detection and tracking of aerial vehicles

Cho

Huh

Choi

et al. 2011

IEEE Conference on Decision and Control and European Control Conference

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show abstract

“…These studies include a formation flight experiment with UAVs utilizing bidirectional communication, and a guidance system utilizing relative velocity, attitude, and the position of the leader [1][2][3][4][5][6][7][8]. Sending and receiving its own position and attitude data through communication between the leader and follower and use the relative values.…”

Section: Introductionmentioning

confidence: 99%

Monocular Vision-Based Guidance and Control for a Formation Flight

Cheon¹,

Kim

Min³

et al. 2015

International Journal of Aeronautical and Space Sciences

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This paper describes a monocular vision-based formation flight technology using two fixed wing unmanned aerial vehicles. To measuring relative position and attitude of a leader aircraft, a monocular camera installed in the front of the follower aircraft captures an image of the leader, and position and attitude are measured from the image using the KLT feature point tracker and POSIT algorithm. To verify the feasibility of this vision processing algorithm, a field test was performed using two light sports aircraft, and our experimental results show that the proposed monocular vision-based measurement algorithm is feasible. Performance verification for the proposed formation flight technology was carried out using the X-Plane flight simulator. The formation flight simulation system consists of two PCs playing the role of leader and follower. When the leader flies by the command of user, the follower aircraft tracks the leader by designed guidance and a PI control law, and all the information about leader was measured using monocular vision. This simulation shows that guidance using relative attitude information tracks the leader aircraft better than not using attitude information. This simulation shows absolute average errors for the relative position as follows: X-axis: 2.88 m, Y-axis: 2.09 m, and Z-axis: 0.44 m.

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An Implementation of Formation Flight Control System Using Two Drones

Kim¹,

Park²

2016

IEMEK Journal of Embedded Systems and Applications

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: In this study, we implemented a formation flight control system using two drones.Ground control system communicates with drones by MAVLink protocol, does keep watch on drone's status and sends simultaneously formation flight instructions to drones in real time. Two drones have been able to fly by a formation flight algorithm without crashing while maintaining the same speed, and a constant distance and altitude.

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Leader - Follower based Formation Guidance Law and Autonomous Formation Flight Test of Multiple MAVs

Cited by 5 publications

References 3 publications

An image processing algorithm for detection and tracking of aerial vehicles

An image processing algorithm for detection and tracking of aerial vehicles

Monocular Vision-Based Guidance and Control for a Formation Flight

An Implementation of Formation Flight Control System Using Two Drones

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