Quadrotor Autonomous Approaching and Landing on a Vessel Deck

Wang, Liyang; Bai, Xiaoli

doi:10.1007/s10846-017-0757-5

Cited by 37 publications

(24 citation statements)

References 21 publications

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“…Quadcopters are an important class of UAVs that are superior in many ways: they have a simple structure, are quick to manufacture, and are inexpensive [4,5]. Controlling their position, in general, and altitude, in particular, has been the subject of numerous studies [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] with ever more advanced algorithms having been proposed to address the quadcopter control problem.…”

Section: Introductionmentioning

confidence: 99%

Improved Altitude Control Algorithm for Quadcopter Unmanned Aerial Vehicles

Xuan-Mung

Hong

2019

Applied Sciences

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Quadcopter unmanned aerial vehicles continue to play important roles in several applications and the improvement of their control performance has been explored in a great number of studies. In this paper, we present an altitude control algorithm for quadcopters that consists of a combination of nonlinear and linear controllers. The smooth transition between the nonlinear and linear modes are guaranteed through controller gains that are obtained based on mathematical analysis. The proposed controller takes advantage and addresses some known shortcomings of the conventional proportional–integral–derivative control method. The algorithm is simple to implement, and we prove its stability through the Lyapunov theory. By prescribing certain flight conditions, we use numerical simulations to compare the control performance of our control method to that of a conventional proportional–derivative–integral approach. Furthermore, we use a DJI-F450 drone equipped with a laser ranging sensor as the experimental quadcopter platform to evaluate the performance of our new controller in real flight conditions. Numerical simulation and experimental results demonstrate the effectiveness of the proposed algorithm.

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Section: Introductionmentioning

confidence: 99%

Improved Altitude Control Algorithm for Quadcopter Unmanned Aerial Vehicles

Xuan-Mung

Hong

2019

Applied Sciences

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“…The purpose is to reduce the sensitivity of drone motion changes in ship parameters. Wang Liyang and other scholars [15] proposed a drone autonomous landing system based on airborne monocular vision, which can improve the ability of autonomous tracking and landing for drones under simulated sea conditions. Moriarty, P et al [16] provided an artificial neural network-based autonomous landing method for UAVs.…”

Section: Introductionmentioning

confidence: 99%

Research on Optimal Landing Trajectory Planning Method between an UAV and a Moving Vessel

Tan

Yang

et al. 2019

Applied Sciences

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The location, velocity, and flight path angle of an autonomous unmanned aerial vehicle (UAV) landing on a moving vessel are key factors for an optimal landing trajectory. To tackle this challenge, this paper proposes a method for calculating the optimal approach landing trajectory between an UAV and a small vessel. A numerical approach (iterative method) is used to calculate the optimal approach landing trajectory, and the initial lead is introduced in the calculation process of the UAV trajectory for the inclination and heading angle for accuracy improvement, so that the UAV can track and calculate the optimal landing trajectory with high precision. Compared with the variational method, the proposed method can calculate an optimal turning direction angle for the UAV during the landing. Simulation experiments verify the effectiveness of the proposed algorithm and give optimal initialization values.

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“…Wang [27] is able to perform the same applications as this thesis using a vision system. Wang is able to achieve an average error in hover of less than 2 cm for a stationary target and less than 3 cm for a moving target.…”

Section: Discussionmentioning

confidence: 96%

“…There are not any reported accuracies related with this system. Wang [27] successfully lands a quadrotor using vision-based methods on a vessel deck by incorporating the motions of the vessel. In flight hover accuracy is assessed with a stationary platform and a moving platform using a Vicon motion capture system to assess the accuracy.…”

Section: 2 the Controller Uses Gps Or An-mentioning

confidence: 99%

“…But this provides the possibility of tracking a moving object or landing on a moving object. Currently vision systems are capable of this[27], but the ultrasonic solution requires less computer processing and works in foggy environments.For this localization method, the ranging technique selected is ToF because it provides fast results with fewer receivers. The clocks are synchronized using a radio frequency signal propagating at the speed of light which is considered instantaneous relative to the speed of sound.…”

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confidence: 99%

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Ultrasonic Localization of a Quadrotor Using a Portable Beacon

O’Keefe¹

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This thesis presents a method for localization of a quadrotor using ultrasound with five receiving nodes and a portable beacon. The time of flight is measured from when the ultrasonic signal is produced to when it is received and triggered through threshold detection. Two different lateration algorithms are explored to determine the position, the analytical trilateration and linear least squares method. The linear least squares algorithm outperforms the analytical trilateration method for static position testing and GPS-denied hover. A new approach named the combined lateration algorithm combines these two methods and has the best stationary standard deviation with 8.0 cm within a one metre radius at a height of 1.77 m. It calculates a successful measurement 93% of the time, which provides an average update rate of 9.3 Hz.Successful autonomous hover and landing is performed using a stationary and moving beacon within a GPS-denied environment.iii There are so many people who have helped me through my journey at Carleton University. To start, I would like to thank Carleton University for providing a fantastic learning experience through my Undergraduate and masters degree.A massive thanks goes to Professor Jason Etele who has been an excellent mentor throughout my degree. I'm still amazed at the ability to break down a problem to its roots and solve it methodically. I always enjoy the presentation dry runs where you completely reorganize presentations in a clearer manner. I am thankful for the research opportunity you provided through a project I am genuinely interested in with the ability to grow and learn new skills. The opportunity you provided to travel to San Diego and present at AIAA was phenomenal. The rowing chats are fun and have given me a benchmark to strive for when I take up rowing.A huge thanks goes to Ali Raza for the continuous support and help throughout my degree. From the very beginning you were excited to explain everything about TARA and your patience was incredible. You were always ready and willing to video chat when I was running into problems and provided great insight. Your experience with controllers was incredibly helpful while tuning my own PID controllers. You provided me with a great start with access to TARA 1 and a preliminary version of the ultrasonic localization system. Many thanks to Mark Sutherland who designed and built TARA 3 which I used for most of my testing. Thanks for providing me ideas on the first steps on integrating iv the ultrasonic localization system on TARA 3.A special thanks goes to the RUAS group, more specifically Brian Lemky and Craig Osborn. They developed the idea of the ultrasonic localization and provided a first version of the system.A massive thanks to Nagui Mikhail, who without I'd still be playing around on a breadboard. You were a massive help with developing my first PCB and troubleshooting the issues along the way. Beforehand I didn't even know how to solder or even what a PCB stood for.

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Quadrotor Autonomous Approaching and Landing on a Vessel Deck

Cited by 37 publications

References 21 publications

Improved Altitude Control Algorithm for Quadcopter Unmanned Aerial Vehicles

Improved Altitude Control Algorithm for Quadcopter Unmanned Aerial Vehicles

Research on Optimal Landing Trajectory Planning Method between an UAV and a Moving Vessel

Ultrasonic Localization of a Quadrotor Using a Portable Beacon

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