Autonomous landing of a VTOL UAV on a moving platform using image-based visual servoing

Author(s):  
Daewon Lee ◽  
Tyler Ryan ◽  
H. Jin. Kim
2017 ◽  
Vol 5 (1) ◽  
pp. 13-26 ◽  
Author(s):  
Iryna Borshchova ◽  
Siu O’Young

In this paper, a method to control a small multi-rotor unmanned aerial system (UAS) while landing on a moving platform using image-based visual servoing is described. The landing scheme is based on positioning visual markers on a landing platform in the form of a detectable pattern. When the onboard camera detects the object pattern, the flight control algorithm will send visual-based servo-commands to align the multi-rotor with the targets. The main contribution is that the proposed method is less computationally expensive as it uses color-based object detection applied to a geometric pattern instead of feature tracking algorithms. This method has the advantage that it does not demand calculating the distance to the objects (depth). The proposed method was tested in simulation using a quadcopter model in V-REP (virtual robotics experimental platform) working in parallel with robot operating system (ROS). Finally, this method was validated in a series of real-time experiments with a quadcopter.


2017 ◽  
Vol 5 (1) ◽  
pp. 28-42 ◽  
Author(s):  
Iryna Borshchova ◽  
Siu O’Young

Purpose The purpose of this paper is to develop a method for a vision-based automatic landing of a multi-rotor unmanned aerial vehicle (UAV) on a moving platform. The landing system must be highly accurate and meet the size, weigh, and power restrictions of a small UAV. Design/methodology/approach The vision-based landing system consists of a pattern of red markers placed on a moving target, an image processing algorithm for pattern detection, and a servo-control for tracking. The suggested approach uses a color-based object detection and image-based visual servoing. Findings The developed prototype system has demonstrated the capability of landing within 25 cm of the desired point of touchdown. This auto-landing system is small (100×100 mm), light-weight (100 g), and consumes little power (under 2 W). Originality/value The novelty and the main contribution of the suggested approach are a creative combination of work in two fields: image processing and controls as applied to the UAV landing. The developed image processing algorithm has low complexity as compared to other known methods, which allows its implementation on general-purpose low-cost hardware. The theoretical design has been verified systematically via simulations and then outdoors field tests.


Author(s):  
José Joaquín Acevedo ◽  
Manuel García ◽  
Antidio Viguria ◽  
Pablo Ramón ◽  
Begoña C. Arrue ◽  
...  

2019 ◽  
Vol 119 ◽  
pp. 64-76 ◽  
Author(s):  
Yuhua Qi ◽  
Jiaqi Jiang ◽  
Jin Wu ◽  
Jianan Wang ◽  
Chunyan Wang ◽  
...  

2016 ◽  
Vol 85 (2) ◽  
pp. 369-384 ◽  
Author(s):  
Oualid Araar ◽  
Nabil Aouf ◽  
Ivan Vitanov

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