Quadrotor UAV Control for Vision-based Moving Target Tracking Task PDF Download

Author: Denys Bohdanov
Publisher:
ISBN: 9780494851708
Category :
Languages : en
Pages :

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Author: Marinela Georgieva Popova
Publisher:
ISBN:
Category :
Languages : en
Pages :

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Author: Kevin Ling
Publisher:
ISBN:
Category :
Languages : en
Pages : 59

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Book Description
With the use of unmanned aerial vehicles (UAVs) becoming more widespread, a need for precise autonomous landings has arisen. In the maritime setting, precise autonomous landings will help to provide a safe way to recover UAVs deployed from a ship. On land, numerous applications have been proposed for UAV and unmanned ground vehicle (UGV) teams where autonomous docking is required so that the UGVs can either recover or service a UAV in the field. Current state of the art approaches to solving the problem rely on expensive inertial measurement sensors and RTK or differential GPS systems. However, such a solution is not practical for many UAV systems. A framework to perform precision landings on a moving target using low-cost sensors is proposed in this thesis. Vision from a downward facing camera is used to track a target on the landing platform and generate high quality relative pose estimates. The landing procedure consists of three stages. First, a rendezvous stage commands the quadrotor on a path to intercept the target. A target acquisition stage then ensures that the quadrotor is tracking the landing target. Finally, visual measurements of the relative pose to the landing target are used in the target tracking stage where control and estimation are performed in a body-planar frame, without the use of GPS or magnetometer measurements. A comprehensive overview of the control and estimation required to realize the three stage landing approach is presented. Critical parts of the landing framework were implemented on an AscTec Pelican testbed. The AprilTag visual fiducial system is chosen for use as the landing target. Implementation details to improve the AprilTag detection pipeline are presented. Simulated and experimen- tal results validate key portions of the landing framework. The novel relative estimation scheme is evaluated in an indoor positioning system. Tracking and landing on a moving target is demonstrated in an indoor environment. Outdoor tests also validate the target tracking performance in the presence of wind.

Author: Liang Yan
Publisher: Springer Nature
ISBN: 981158155X
Category : Technology & Engineering
Languages : en
Pages : 5416

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This book features the latest theoretical results and techniques in the field of guidance, navigation, and control (GNC) of vehicles and aircraft. It covers a range of topics, including, but not limited to, intelligent computing communication and control; new methods of navigation, estimation, and tracking; control of multiple moving objects; manned and autonomous unmanned systems; guidance, navigation, and control of miniature aircraft; and sensor systems for guidance, navigation, and control. Presenting recent advances in the form of illustrations, tables, and text, it also provides detailed information of a number of the studies, to offer readers insights for their own research. In addition, the book addresses fundamental concepts and studies in the development of GNC, making it a valuable resource for both beginners and researchers wanting to further their understanding of guidance, navigation, and control.

Author: Jianglong Yu
Publisher: Springer Nature
ISBN: 9819733324
Category :
Languages : en
Pages : 700

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Author: Hani Hunud Abia Kadouf
Publisher:
ISBN:
Category :
Languages : en
Pages : 220

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Useful applications of Unmanned Air Vehicles (UAVs) include aerial surveillance in hostile military zones or search and rescue operations in disaster stricken areas. The increased visual capacity of UAVs also helps support ground vehicles during scouting missions or to extend communication beyond insurmountable land or water barriers. Computer vision techniques provide a simplistic means to convey information for motion control of a UAV. Hence this work focuses on the development of a vision based image processing algorithm for autonomous navigation of a quadrotor UAV. A camera was used to capture an aerial field of view and transmit a video stream of its perspective to a base station- where OpenCV 2.3.1 vision processing software was used to implement a vision processing algorithm. The algorithm comprises of colour thresholding, the use of image moment and blob detection to detect and track an object within the camea view. Experimental readings of an object's displacement at three altitudes; 1.5m, 2.0m and 2.5m were used to derive pixel-to-cm conversion equations based on the target's pixel coordinates on the viewing window. Through a statistical analysis of variance and standard deviation conducted on 15 experimental readings of displacement ranging from 5cm to 25cm; it was shown that the vision system is best suited for tracking displacements at lower altitude flights. Hence, the best result for variance and standard were achieved when using the derived equation and were 0.64 and 0.8 respectively. The equation derived was also used to derive GPS locking coordinates. Pixel coordinates of a target on the camera display were then used to produce GPS locking coordinates for the quadrotor to track a target object.

Author: Steven Andrew Provencio Quintero
Publisher:
ISBN: 9781321349955
Category :
Languages : en
Pages : 215

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Small unmanned aerial vehicles (UAVs) are relatively inexpensive mobile sensing platforms capable of reliably and autonomously performing numerous tasks, including mapping, search and rescue, surveillance and tracking, and real-time monitoring. The general problem of interest that we address is that of using small, fixed-wing UAVs to perform vision-based target tracking, which entails that one or more camera-equipped UAVs is responsible for autonomously tracking a moving ground target. In the single-UAV setting, the underactuated UAV must maintain proximity and visibility of an unpredictable ground target while having a limited sensing region. We provide solutions from two different vantage points. The first regards the problem as a two-player zero-sum game and the second as a stochastic optimal control problem. The resulting control policies have been successfully field-tested, thereby verifying the efficacy of both approaches while highlighting the advantages of one approach over the other.

Author: Luis Rodolfo García Carrillo
Publisher: Springer Science & Business Media
ISBN: 144714399X
Category : Technology & Engineering
Languages : en
Pages : 191

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Book Description
Quad Rotorcraft Control develops original control methods for the navigation and hovering flight of an autonomous mini-quad-rotor robotic helicopter. These methods use an imaging system and a combination of inertial and altitude sensors to localize and guide the movement of the unmanned aerial vehicle relative to its immediate environment. The history, classification and applications of UAVs are introduced, followed by a description of modelling techniques for quad-rotors and the experimental platform itself. A control strategy for the improvement of attitude stabilization in quad-rotors is then proposed and tested in real-time experiments. The strategy, based on the use low-cost components and with experimentally-established robustness, avoids drift in the UAV’s angular position by the addition of an internal control loop to each electronic speed controller ensuring that, during hovering flight, all four motors turn at almost the same speed. The quad-rotor’s Euler angles being very close to the origin, other sensors like GPS or image-sensing equipment can be incorporated to perform autonomous positioning or trajectory-tracking tasks. Two vision-based strategies, each designed to deal with a specific kind of mission, are introduced and separately tested. The first stabilizes the quad-rotor over a landing pad on the ground; it extracts the 3-dimensional position using homography estimation and derives translational velocity by optical flow calculation. The second combines colour-extraction and line-detection algorithms to control the quad-rotor’s 3-dimensional position and achieves forward velocity regulation during a road-following task. In order to estimate the translational-dynamical characteristics of the quad-rotor (relative position and translational velocity) as they evolve within a building or other unstructured, GPS-deprived environment, imaging, inertial and altitude sensors are combined in a state observer. The text give the reader a current view of the problems encountered in UAV control, specifically those relating to quad-rotor flying machines and it will interest researchers and graduate students working in that field. The vision-based control strategies presented help the reader to a better understanding of how an imaging system can be used to obtain the information required for performance of the hovering and navigation tasks ubiquitous in rotored UAV operation.

Author: Mohsen Majnoon
Publisher:
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
Control of unmanned aerial vehicles is a very active topic in research with lots of applications ranging from civilian to military. To control a UAV, its attitude is often controlled using gyroscopes, but to control its position, inertial sensors together with GPS are often used. However, obtaining accurate current position is difficult using inertial sensors because of the integration drift. GPS on the other hand is not functional in indoor applications since it cannot connect to GPS satellites. Since vision has been proved to be an inexpensive and consistent source of relative position information, vision-based control is getting more popular in UAVs recently, but then again, using vision in outdoor applications is challenging as the target can move fast and out of the vision sensor field of view. So, in order to keep the target inside the field of view, two algorithms are being developed and tested via simulation in this research. Using pan/tilt/zoom cameras or multi camera systems, the target is guaranteed to stay in vision system field of view and hence, the vision based pose estimation can provide the control system with proper relative position. Two case studies - vision-based mobile-target tracking of a quadrotor using a multi-camera vision sensor and vision-based mobile-target tracking of a tilting rotor aircraft equipped with a zooming camera - are presented in this research to show the applicability of these methods in UAV control.

Author: Ruoyu Tan
Publisher:
ISBN:
Category :
Languages : en
Pages : 95

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Book Description
An Unmanned Air Vehicle (UAV) is an aircraft without a human pilot on board. It can be controlled either autonomously by computers onboard, or using a remote control by a pilot on the ground, or in another vehicle. In both military and civilian sectors, UAVs are quickly obtaining popularity and expected to expand dramatically in the years to come. As UAVs gain more attention, one of the immediate requirements would be to have UAVs work as much autonomously as possible. One of the common tasks that UAVs would be engaged in is target tracking which has various potential applications in military field, law-enforcement, wildlife protection effort, and so on. This thesis focuses on development of a controller for UAVs to track ground target. In particular, this thesis focuses on quadrotor UAV, which is a multicopter that is lifted and propelled using four motors. Admittedly, several target tracking control methods have been developed in recent years. However, only a few of them have been applied on a quadrotor. Most of these tracking methods, particularly those based on Proportional Derivative (PD) control laws, which have been applied on quadrotors, are not time efficient due to practical acceleration constraint and a number of parameters that need to be tuned. The UAV control problem can be divided into 4 sub-problems: Position Control, Motor Control, Trajectory Tracking and Trajectory Generation. In this thesis, the dynamic equations of motion for quadrotors and a Proportional Derivative control law is derived to solve the problems of Position Control, Motor Control and Trajectory Tracking. A Proportional Navigation (PN) based switching strategy is proposed to address the problem of Trajectory Generation. The experiments and numerical simulations are performed using non-maneuvering and maneuvering targets. The simulation results show that the proposed PN based switching strategy not only carries out effective tracking but also results into smaller oscillations and errors when compared to the widely used PD tracking method. The switching strategy, as proposed as a solution to target tracking problem, leaves an important question with regard to when should the switching happen. It is intuitive that the time of switching will play a role in how fast the UAV converges to the target. The second problem considered in this thesis relates to the optimal time of switching that would minimize the positional error between the UAV and the target. An optimal switching strategy is proposed to obtain the optimal switching time for both non-maneuvering and maneuvering targets. Analytical solutions that generate trajectories based on PN and PD methods are used in this strategy. The numerical simulations validate the optimality, reliability, and accuracy of the proposed method for both non-maneuvering and maneuvering targets.