scholarly journals Unmanned Aerial Vehicle Surveillance Under Visibility and Dwell-Time Constraints

2019 ◽  
Vol 141 (6) ◽  
Author(s):  
Jeffrey R. Peters ◽  
Amit Surana ◽  
Grant S. Taylor ◽  
Terry S. Turpin ◽  
Francesco Bullo
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Dwell Time ◽  
Visual Surveillance ◽  
Graph Search ◽  
Routing Problem ◽  
Numerical Studies ◽  
Aerial Vehicle ◽  
Time Required ◽  
Discrete Graph ◽  
Initial Target

A framework is introduced for planning unmanned aerial vehicle (UAV) flight paths for visual surveillance of ground targets, each having particular viewing requirements. Specifically, the framework is designed for instances in which each target is associated with a set of imaging parameters, including a desired: (i) tilt angle, (ii) azimuth, with the option of a 360 deg view, and (iii) dwell-time. Tours are sought to image the targets, while minimizing both the total mission time and the time required to reach the initial target. An ϵ-constraint scalarization is used to pose the multi-objective problem as a constrained optimization, which, through careful discretization, can be approximated as a discrete graph-search. It is shown that, in many cases, this approximation is equivalent to a generalized traveling salesperson problem (GTSP). A heuristic procedure for solving the discrete approximation and recovering solutions to the full routing problem is presented and illustrated through numerical studies.

Design and Manufacture of a Miniature UAV Using 3D Rapid Prototyping

2011 ◽  
Vol 308-310 ◽  
pp. 1426-1435 ◽  
Author(s):  
Zahari Taha ◽  
Vin Cent Tai ◽  
Phen Chiak See
Keyword(s):  
Rapid Prototyping ◽  
Unmanned Aerial Vehicle ◽  
Acrylonitrile Butadiene Styrene ◽  
Main Motivation ◽  
Design Specifications ◽  
Rapid Product Development ◽  
Aerial Vehicle ◽  
Time Required ◽  
Design And Manufacture ◽  
Butadiene Styrene

This paper describes the design and manufacture of a Miniature Unmanned Aerial Vehicle (MUAV) using the StratasysTM 3D Rapid Prototyping (RP) machine. The main motivation for this work is to demonstrate the rapid product development capabilities of the machine. The polymeric material used in this process is Acrylonitrile-Butadiene-Styrene (ABS). Its superior properties allow the MUAV structure to be built accurately to design specifications. The advantage of this approach is the shorter time required for design, fabrication and deployment.

The estimation algorithm of operative capabilities of complex countermeasures to resist UAVs

SIMULATION ◽  
2018 ◽  
Vol 95 (6) ◽  
pp. 569-573
Author(s):  
Igor Korobiichuk ◽  
Yuriy Danik ◽  
Oleksyj Samchyshyn ◽  
Sergiy Dupelich ◽  
Maciej Kachniarz
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Estimation Algorithm ◽  
Probability Of Detection ◽  
Software Implementation ◽  
Observation Model ◽  
Different Types ◽  
Aerial Vehicle ◽  
Use Efficiency ◽  
Time Required

The proposed observation model provides for calculating the probability of detection of different types of unmanned aerial vehicle (UAV) at a certain range with regard to their tactical and technical characteristics and security equipment capabilities. The comparison of the obtained values of generalized indicators of security equipment use efficiency is based on a specified criterion. To take into account factors that significantly affect a modeling object, calculations are carried out under specified conditions and restrictions. UAVs should be detected until a covering object gets in a swath width given the time required for countermeasures. Based on the software implementation of the algorithm we have evaluated the efficiency of use of hypothetical security equipment for detecting certain types of UAVs, and defined means of further use or improvement.

scholarly journals Modelling of time-to collision for unmanned aerial vehicle using particles swarm optimization

2020 ◽  
Vol 9 (3) ◽  
pp. 488
Author(s):  
Sulaiman Bin Sabikan ◽  
Nawawi. S. W ◽  
NAA Aziz
Keyword(s):  
Mathematical Model ◽  
Unmanned Aerial Vehicle ◽  
Pso Algorithm ◽  
Swarm Optimization ◽  
Time To Collision ◽  
Optimal Linear ◽  
Aerial Vehicle ◽  
Receiver Unit ◽  
Braking Control ◽  
Time Required

A method for the development of Time-to-Collision (TTC) mathematical model for outdoor Unmanned Aerial Vehicle (UAV) using Particles Swarm Optimization (PSO), are presented. TTC is the time required for a UAV either to collide with any static obstacle or completely stop without applying any braking control system when the throttle is fully released. This model provides predictions of time before UAV will collide with the obstacle in the same path based on their parameter, for instance, current speed and payload. However, this paper focus on the methodology of the implementation of PSO to develop the TTC model for 5 different set of payloads. This work utilizes a quadcopter as our testbed system, that equipped with a Global Positioning System (GPS) receiver unit, a flight controller with data recording capability and ground control station for real-time monitoring. The recorded onboard flight mission data for 5 different set of payloads has been analyzed to develop a mathematical model of TTC through the PSO approach. The horizontal ground speed, throttle magnitudes and flight time stamp are extracted from the on-board quadcopter flight mission. PSO algorithm is used to find the optimal linear TTC model function, while the mean square error is used to evaluate the best fitness of the solution. The results of the TTC mathematical model for each payload are described.

scholarly journals The Human—Unmanned Aerial Vehicle System Based on SSVEP—Brain Computer Interface

Electronics ◽  
2021 ◽  
Vol 10 (23) ◽  
pp. 3025
Author(s):  
Ming-An Chung ◽  
Chia-Wei Lin ◽  
Chih-Tsung Chang
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Visual Stimulation ◽  
Brain Computer Interface ◽  
Computer Interface ◽  
Left Turn ◽  
Practical Applications ◽  
Aerial Vehicle ◽  
Time Required ◽  
Physically Challenged ◽  
The Brain

The brain–computer interface (BCI) is a mechanism for extracting information from the brain, with this information used for various applications. This study proposes a method to control an unmanned aerial vehicle (UAV) flying through a BCI system using the steady-state visual evoked potential (SSVEP) approach. The UAV’s screen emits three frequencies for visual stimulation: 15, 23, and 31 Hz for the UAV’s left-turn, forward-flight, and right-turn functions. Due to the requirement of immediate response to the UAV flight, this paper proposes a method to improve the accuracy rate and reduce the time required to correct instruction errors in the resolution of brainwave signals received by UAVs. This study tested ten subjects and verified that the proposed method has a 10% improvement inaccuracy. While the traditional method can take 8 s to correct an error, the proposed method requires only 1 s, making it more suitable for practical applications in UAVs. Furthermore, such a BCI application for UAV systems can achieve the same experience of using the remote control for physically challenged patients.

scholarly journals Impact of UAV Delivery on Sustainability and Costs under Traffic Restrictions

2020 ◽  
Vol 2020 ◽  
pp. 1-15
Author(s):  
Yuyu Li ◽  
Wei Yang ◽  
Bo Huang
Keyword(s):  
Genetic Algorithm ◽  
Energy Consumption ◽  
Unmanned Aerial Vehicle ◽  
Environmental Sustainability ◽  
Mixed Integer ◽  
Environmental Aspects ◽  
Routing Problem ◽  
Vehicle Type ◽  
Aerial Vehicle ◽  
Reduce Energy Consumption

Compared with traditional vehicles delivery, unmanned aerial vehicle (UAV) delivery can reduce energy consumption and greenhouse gas emissions, which benefits environmental sustainability. Besides, UAVs can overcome traffic restrictions, which are the big obstacle in parcel delivery. In reality, there are two kinds of most popular traffic restrictions, vehicle-type restriction, and half-side traffic. We propose a mixed-integer (0-1 linear) green routing model with these two kinds of traffic restrictions for UAVs to exploit the environmental aspects of the use of UAVs in logistics. A genetic algorithm is proposed to efficiently solve the complex routing problem, and an experimental analysis is made to illustrate and validate our model and the algorithm. We found that, under both these two traffic restrictions, UAV delivery can accomplish deliveries that cannot be carried out or are carried out at much higher costs by vehicles only and can always effectively save costs and cut CO2 emissions, which is environmentally friendly. Furthermore, UAV delivery saves more cost and cuts more CO2 emission under the first kind of traffic restriction than that under the second.

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