1,293 research outputs found
A survey on fractional order control techniques for unmanned aerial and ground vehicles
In recent years, numerous applications of science and engineering for modeling and control of unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) systems based on fractional calculus have been realized. The extra fractional order derivative terms allow to optimizing the performance of the systems. The review presented in this paper focuses on the control problems of the UAVs and UGVs that have been addressed by the fractional order techniques over the last decade
Effective Target Aware Visual Navigation for UAVs
In this paper we propose an effective vision-based navigation method that
allows a multirotor vehicle to simultaneously reach a desired goal pose in the
environment while constantly facing a target object or landmark. Standard
techniques such as Position-Based Visual Servoing (PBVS) and Image-Based Visual
Servoing (IBVS) in some cases (e.g., while the multirotor is performing fast
maneuvers) do not allow to constantly maintain the line of sight with a target
of interest. Instead, we compute the optimal trajectory by solving a non-linear
optimization problem that minimizes the target re-projection error while
meeting the UAV's dynamic constraints. The desired trajectory is then tracked
by means of a real-time Non-linear Model Predictive Controller (NMPC): this
implicitly allows the multirotor to satisfy both the required constraints. We
successfully evaluate the proposed approach in many real and simulated
experiments, making an exhaustive comparison with a standard approach.Comment: Conference paper at "European Conference on Mobile Robotics" (ECMR)
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Vision-Based Autonomous Landing of a Quadrotor on the Perturbed Deck of an Unmanned Surface Vehicle
Autonomous landing on the deck of an unmanned surface vehicle (USV) is still a major challenge for unmanned aerial vehicles (UAVs). In this paper, a fiducial marker is located on the platform so as to facilitate the task since it is possible to retrieve its six-degrees of freedom relative-pose in an easy way. To compensate interruption in the marker’s observations, an extended Kalman filter (EKF) estimates the current USV’s position with reference to the last known position. Validation experiments have been performed in a simulated environment under various marine conditions. The results confirmed that the EKF provides estimates accurate enough to direct the UAV in proximity of the autonomous vessel such that the marker becomes visible again. Using only the odometry and the inertial measurements for the estimation, this method is found to be applicable even under adverse weather conditions in the absence of the global positioning system
Asymptotic Vision-Based Tracking Control of the Quadrotor Aerial Vehicle
This paper proposes an image-based visual servo (IBVS) controller for the 3D translational
motion of the quadrotor unmanned aerial vehicle (UAV). The main purpose of this paper is to
provide asymptotic stability for vision-based tracking control of the quadrotor in the presence
of uncertainty in the dynamic model of the system. The aim of the paper also includes the use
of
ow of image features as the velocity information to compensate for the unreliable linear
velocity data measured by accelerometers. For this purpose, the mathematical model of the
quadrotor is presented based on the optic
ow of image features which provides the possibility
of designing a velocity-free IBVS controller with considering the dynamics of the robot. The
image features are de ned from a suitable combination of perspective image moments without
using the model of the object. This property allows the application of the proposed controller
in unknown places. The controller is robust with respect to the uncertainties in the transla-
tional dynamics of the system associated with the target motion, image depth and external
disturbances. Simulation results and a comparison study are presented which demonstrate the
e ectiveness of the proposed approach
Towards an autonomous vision-based unmanned aerial system againstwildlife poachers
Poaching is an illegal activity that remains out of control in many countries. Based on the 2014 report of the United Nations and Interpol, the illegal trade of global wildlife and natural resources amounts to nearly $213 billion every year, which is even helping to fund armed conflicts. Poaching activities around the world are further pushing many animal species on the brink of extinction. Unfortunately, the traditional methods to fight against poachers are not enough, hence the new demands for more efficient approaches. In this context, the use of new technologies on sensors and algorithms, as well as aerial platforms is crucial to face the high increase of poaching activities in the last few years. Our work is focused on the use of vision sensors on UAVs for the detection and tracking of animals and poachers, as well as the use of such sensors to control quadrotors during autonomous vehicle following and autonomous landing.Peer Reviewe
Design and Demonstration of a Two-Dimentional Test Bed for UAV Controller Evaluation
A three degree-of-freedom (DOF) planar test bed for Unmanned Aerial Vehicle (UAV) controller evaluation was built. The test-bed consists of an instrumented tether and an experimental twin-rotor, planar UAV mounted with a one DOF manipulator mounted below the UAV body. The tether was constructed to constrain the UAV under test to motion on the surface of a sphere. Experiments can be conducted through the tether, approximating motion in a vertical plane by a UAV under test. The tether provides the means to measure the position and attitude of the UAV under test. The experimental twin-rotor UAV and one-link on-board manipulator, were designed and built to explore a unified control strategy for Manipulator on VTOL Aircraft (MOVA), in which the interaction of UAV body dynamics with the manipulator motion is of primary interest. The dynamics of the propulsion unit was characterized through experiments, based on which a phase lead compensator was designed to improve the UAV frequency response. A \u27separate\u27 controller based on independent nonlinear control of the VTOL aircraft and PD linear control of the on-board manipulator was designed as a reference for comparison to the unified MOVA controller. Tests with the separate controller show the negative effect that a coupled manipulator can have on the UAV body motion, while the tests on MOVA show the potential benefit of explicit compensation of the UAV and manipulator interaction
Survey of computer vision algorithms and applications for unmanned aerial vehicles
This paper presents a complete review of computer vision algorithms and vision-based intelligent applications, that are developed in the field of the Unmanned Aerial Vehicles (UAVs) in the latest decade. During this time, the evolution of relevant technologies for UAVs; such as component miniaturization, the increase of computational capabilities, and the evolution of computer vision techniques have allowed an important advance in the development of UAVs technologies and applications. Particularly, computer vision technologies integrated in UAVs allow to develop cutting-edge technologies to cope with aerial perception difficulties; such as visual navigation algorithms, obstacle detection and avoidance and aerial decision-making. All these expert technologies have developed a wide spectrum of application for UAVs, beyond the classic military and defense purposes. Unmanned Aerial Vehicles and Computer Vision are common topics in expert systems, so thanks to the recent advances in perception technologies, modern intelligent applications are developed to enhance autonomous UAV positioning, or automatic algorithms to avoid aerial collisions, among others. Then, the presented survey is based on artificial perception applications that represent important advances in the latest years in the expert system field related to the Unmanned Aerial Vehicles. In this paper, the most significant advances in this field are presented, able to solve fundamental technical limitations; such as visual odometry, obstacle detection, mapping and localization, et cetera. Besides, they have been analyzed based on their capabilities and potential utility. Moreover, the applications and UAVs are divided and categorized according to different criteria.This research is supported by the Spanish Government through the CICYT projects (TRA2015-63708-R and TRA2013-48314-C3-1-R)
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