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This paper presents a nonlinear model predictive controller to follow desired 3D trajectories with the end effector of an unmanned aerial manipulator (i.e., a multirotor with a serial arm attached). To the knowledge of the authors, this is the first time that such controller runs online and on board a limited computational unit to drive a kinematically augmented aerial vehicle. Besides the trajectory...
This paper presents a neural network based model reference adaptive controller (MRAC) for the control of a fixed-wing unmanned aerial vehicle (UAV). An adaptive neural network is trained using the error between the UAV response and the desired response as given by the reference model. The design of a suitable reference model for the desired aircraft performance is investigated and developed. Unknown...
In this work, we present an autonomous control system to perform aerobatic maneuvers with an agile fixed-wing UAV. The control system is strongly based on the underlying physics of the aircraft, thus allowing simple control techniques to work well through the full range of flight conditions undergone in aerobatic maneuvers. Moreover, this single control system is capable of performing a wide variety...
A modern class of small fixed-wing unmanned aerial vehicles are physically capable of performing exceptional aerobatic maneuvers. This paper presents a methodology for including one of the more functional of these maneuvers, the knife-edge, in motion planning. This is achieved by separating the top-level motion planner from the dynamics and control of the knife-edge maneuver. By coupling feedback...
A nonlinear adaptive controller for an unmanned aerial vehicle (UAV) has been developed using Echo State Network (ESN), which is a form of three-layered recurrent neural network (RNN). Online learning is used to train the ESN in real-time starting from randomized weights. The ESN is integrated into ArduPilot, an open source autopilot, for complex flight simulations. Software-in-the-loop and hardware-...
An Unmanned Aircraft System (UAS) is a Cyber- Physical System (CPS) in which a host of real-time computational tasks contending for shared resources must be cooperatively managed to provide actuation input for control of the locomotion necessary to obtain mission objectives. Traditionally, control of the UAS is designed assuming a fixed, high sampling rate in order to maintain reliable performance...
This work proposes an adaptive dynamic controller for an unmanned aerial vehicle (UAV) to track a desired trajectory. Initially, reference velocities are generated by a controller that is based only on the kinematic model of the UAV. Subsequently, new control actions are calculated to compensate for the internal dynamics of the robot. Then the model parameters that characterize the robot dynamics...
A controller is designed for hexacopter platform to achieve accurate tracking of altitude and attitude commands under the influence of severe disturbances. The main aim is designing a controller that can be tuned easily to satisfy desired performance requirements. For this purpose, multi-variable control method LQR is combined with PID structure which provides valuable physical insight in tuning process...
In this paper, we present the design and verification of a hybrid vertical takeoff and landing (VTOL) unmanned aerial vehicles (UAV) of the type named dualsystem or extra propulsion VTOL UAV. This paper features the comprehensive system development of such VTOL UAVs from all aspects, including the aircraft design and implementation, onboard devices integration, ground station support, and long distance...
Fully autonomous landing on moving platforms poses a problem of importance for Unmanned Aerial Vehicles (UAVs). Current approaches are usually based on tracking and following the moving platform by means of several techniques, which frequently lack performance in real applications. The aim of this paper is to prove a simple landing strategy is able to provide practical results. The presented approach...
Measuring or estimating adequately and accurately the state of charge (SoC) of a Li-Po battery, which powered an UAV during its flight allows to know the limits of the mission that the UAV is developing and to maximize the energy supplied by the battery. In this sense this paper presents a methodology to estimate the state of charge (SoC) of a Li- Po battery through an Extended Kalman Filter (EKF)...
Early plant disease detection and treatment could dramatically increase crop yield. However, even experts cannot visually distinguish various diseases with certainty, limiting image based diagnosis. In this paper, we present a novel small unmanned aircraft system (sUAS) for phytobiopsy. This platform can remove a leaf section with visual symptoms and transport it to a lab for precise disease analysis...
The wide use of the Global Positioning System (GPS) for navigation has been persistent for a long time. However, in today's scenario when technologies are advancing the accuracy of positioning systems, there are various new threats and challenges emerging. The signal receivers for positioning systems are prone to spoofing. This external interference in the system is usually done by feeding false signals...
This article proposes a control strategy based on the constrained generalized predictive control (GPC) in combination with a geometric attitude controller for trajectory tracking of the quadcopter vehicle. The generalized predictive control approach allows tracking time varying trajectories using optimal control actions to meet constraints on the desired trajectory. The geometric attitude controller...
This paper presents a model-based shadow estimation method that aims at identifying self-cast shadows of aerial vehicles in on-board images. The self-cast shadow poses a non-negligible problem in any kind of on-board processing, e.g. remote sensing, visual odometry, or target tracking. Therefore, it often is necessary to exclude the image regions that contain this self-cast shadow. The presented method...
This paper proposes a novel method for corresponding visual measurements to map points in a visual-inertial navigation system. The algorithm is based on the minimization of the photometric error on sparse locations of the image region, and realizes a gain in robustness that comes from the elimination of the need of feature-extraction for correspondence. The system is compared to a standard approach...
In this paper, a vision-aided terrain referenced navigation (VATRN) algorithm constructed by point-mass filter (PMF) is accelerated by graphic processing unit (GPU). The terrain referenced navigation algorithm estimates the vehicle's position by blending INS data with measured terrain height, and matching that data with the stored digital terrain elevation database (DTED). On the other hands, the...
This paper presents a cooperative navigation technique which exploits relative vision-based sensing and carrier-phase differential GPS (CDGPS) between antennas embarked on different flying platforms, to improve UAV attitude estimation in real time or in post-processing phase. The focus is set on outdoor environments, hence it is assumed that all vehicles are under nominal GPS coverage. The logical...
This paper proposes a solution to the problem of cooperative exploration using an Unmanned Ground Vehicle (UGV) and an Unmanned Aerial Vehicle (UAV). More specifically, the UGV navigates through the free space, and the UAV provides enhanced situational awareness via its higher vantage point. The motivating application is search and rescue in a damaged building. A camera atop the UGV is used to track...
This paper describes a novel vision-based target tracking and landing method that uses aerial images from an on-board camera. The proposed method explicitly deals with occlusions that often occur during these maneuvers. Normalized cross correlation (NCC) is used to locate an image patch in a reference image with a measure of certainty. The key insight is that over the course of the vehicle approach,...
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