A Vision-based Method for Autonomous Landing on a Target with a Quadcopter

Tran, Le-Anh; Le, Ngoc-Phu; Do, Truong-Dong; Le, My-Ha

doi:10.1109/gtsd.2018.8595521

Cited by 11 publications

(2 citation statements)

References 3 publications

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“…Tanaka [ 2 ] also replaced a square of their AR marker with a lenticular angle gauge to improve attitude estimates. Putra et al [ 5 ], Respall et al [ 6 ], and Tran et al [ 7 ] used color detection algorithms to estimate the position of the center of a solid color shape on a contrasting background. Sudevan et al [ 8 ] and Demirhan and Permachandra [ 9 ] used a letter “H” stamped on their ground target for their system to detect the contours of the letter and estimate landing position.…”

Section: Introductionmentioning

confidence: 99%

Precision Landing of a Quadcopter Drone by Smartphone Video Guidance Sensor in a GPS-Denied Environment

Bautista

Gutiérrez

Inness

et al. 2023

Sensors

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This paper describes the deployment, integration, and demonstration of a Smartphone Video Guidance Sensor (SVGS) as a novel technology for autonomous 6-DOF proximity maneuvers and precision landing of a quadcopter drone. The proposed approach uses a vision-based photogrammetric position and attitude sensor (SVGS) to estimate the position of a landing target after video capture. A visual inertial odometry sensor (VIO) is used to provide position estimates of the UAV in a ground coordinate system during flight on a GPS-denied environment. The integration of both SVGS and VIO sensors enables the accurate updating of position setpoints during landing, providing improved performance compared with VIO-only landing, as shown in landing experiments. The proposed technique also shows significant operational advantages compared with state-of-the-art sensors for indoor landing, such as those based on augmented reality (AR) markers.

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Section: Introductionmentioning

confidence: 99%

Precision Landing of a Quadcopter Drone by Smartphone Video Guidance Sensor in a GPS-Denied Environment

Bautista

Gutiérrez

Inness

et al. 2023

Sensors

View full text Add to dashboard Cite

show abstract

“…Autonomous driving vehicles, on the other hand, have been considered the future of technology as they have drawn huge attention for the last decade. Many studies regarding autonomous robots are conducted such as autonomous drones [4] and self-driving cars [5][6][7]. Advanced driver assistance systems (ADAS), consequently, are introduced to improve traffic effectiveness, prevent traffic accidents, and facilitate fully autonomous driving in near future.…”

Section: Introductionmentioning

confidence: 99%

Enhancement of Robustness in Object Detection Module for Advanced Driver Assistance Systems

Tran

Park

et al. 2021

2021 International Conference on System Science and Engineering (ICSSE)

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A unified system integrating a compact object detector and a surrounding environmental condition classifier for enhancing the robustness of object detection scheme in advanced driver assistance systems (ADAS) is proposed in this paper. ADAS are invented to improve traffic safety and effectiveness in autonomous driving systems where the object detection plays an extremely important role. However, modern object detectors integrated in ADAS are still unstable due to high latency and the variation of the environmental contexts in the deployment phase. Our system is proposed to address the aforementioned problems. The proposed system includes two main components: (1) a compact one-stage object detector which is expected to be able to perform at a comparable accuracy compared to state-of-the-art object detectors, and (2) an environmental condition detector that helps to send a warning signal to the cloud in case the self-driving car needs human actions due to the significance of the situation. The empirical results prove the reliability and the scalability of the proposed system to realistic scenarios.

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Fiducial Marker-Based Autonomous Landing Using Image Filter and Kalman Filter

Park

Song

et al. 2023

Int. J. Aeronaut. Space Sci.

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A Vision-based Method for Autonomous Landing on a Target with a Quadcopter

Cited by 11 publications

References 3 publications

Precision Landing of a Quadcopter Drone by Smartphone Video Guidance Sensor in a GPS-Denied Environment

Precision Landing of a Quadcopter Drone by Smartphone Video Guidance Sensor in a GPS-Denied Environment

Enhancement of Robustness in Object Detection Module for Advanced Driver Assistance Systems

Fiducial Marker-Based Autonomous Landing Using Image Filter and Kalman Filter

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