Energy-Aware Trajectory Planning for the Localization of Mobile Devices Using an Unmanned Aerial Vehicle

2016 ◽  
Author(s):  
Oleksandr Artemenko ◽  
Omachonu Joshua Dominic ◽  
Oleksandr Andryeyev ◽  
Andreas Mitschele-Thiel
Keyword(s):  
Mobile Devices ◽  
Unmanned Aerial Vehicle ◽  
Trajectory Planning ◽  
Energy Aware ◽  
Aerial Vehicle

Optimized artificial potential field algorithm to multi-unmanned aerial vehicle coordinated trajectory planning and collision avoidance in three-dimensional environment

2019 ◽  
Vol 233 (16) ◽  
pp. 6032-6043 ◽  
Author(s):  
Jun Tang ◽  
Jiayi Sun ◽  
Cong Lu ◽  
Songyang Lao
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Collision Avoidance ◽  
Unmanned Aerial Vehicle ◽  
Trajectory Planning ◽  
Potential Field ◽  
Three Dimensional ◽  
Artificial Potential Field ◽  
Aerial Vehicles ◽  
Aerial Vehicle ◽  
Vehicle Trajectory

Multi-unmanned aerial vehicle trajectory planning is one of the most complex global optimum problems in multi-unmanned aerial vehicle coordinated control. Results of recent research works on trajectory planning reveal persisting theoretical and practical problems. To mitigate them, this paper proposes a novel optimized artificial potential field algorithm for multi-unmanned aerial vehicle operations in a three-dimensional dynamic space. For all purposes, this study considers the unmanned aerial vehicles and obstacles as spheres and cylinders with negative electricity, respectively, while the targets are considered spheres with positive electricity. However, the conventional artificial potential field algorithm is restricted to a single unmanned aerial vehicle trajectory planning in two-dimensional space and usually fails to ensure collision avoidance. To deal with this challenge, we propose a method with a distance factor and jump strategy to resolve common problems such as unreachable targets and ensure that the unmanned aerial vehicle does not collide into the obstacles. The method takes companion unmanned aerial vehicles as the dynamic obstacles to realize collaborative trajectory planning. Besides, the method solves jitter problems using the dynamic step adjustment method and climb strategy. It is validated in quantitative test simulation models and reasonable results are generated for a three-dimensional simulated urban environment.

scholarly journals Design of facial recognition system implemented in an unmanned aerial vehicle for citizen security in Latin America

2019 ◽  
Vol 27 ◽  
pp. 04002
Author(s):  
Diego Herrera ◽  
Hiroki Imamura
Keyword(s):  
Neural Network ◽  
Latin America ◽  
Deep Learning ◽  
Mobile Devices ◽  
Unmanned Aerial Vehicle ◽  
Facial Recognition ◽  
Recognition System ◽  
Criminal Records ◽  
Aerial Vehicle ◽  
Facial Recognition System

In the new technological era, facial recognition has become a central issue for a great number of engineers. Currently, there are a great number of techniques for facial recognition, but in this research, we focus on the use of deep learning. The problems with current facial recognition convection systems are that they are developed in non-mobile devices. This research intends to develop a Facial Recognition System implemented in an unmanned aerial vehicle of the quadcopter type. While it is true, there are quadcopters capable of detecting faces and/or shapes and following them, but most are for fun and entertainment. This research focuses on the facial recognition of people with criminal records, for which a neural network is trained. The Caffe framework is used for the training of a convolutional neural network. The system is developed on the NVIDIA Jetson TX2 motherboard. The design and construction of the quadcopter are done from scratch because we need the UAV for adapt to our requirements. This research aims to reduce violence and crime in Latin America.

Tactical Trajectory Planning for Stealth Unmanned Aerial Vehicle to Win the Radar Game

2012 ◽  
Vol 62 (6) ◽  
pp. 375-381 ◽  
Author(s):  
Hongfu Liu ◽  
Shaofei Chen ◽  
Lincheng Shen ◽  
Jing Chen
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Trajectory Planning ◽  
Aerial Vehicle

scholarly journals Online Discrete Anchor Graph Hashing for Mobile Person Re-Identification

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Liang Xie ◽  
Xi Fang
Keyword(s):  
Mobile Devices ◽  
Unmanned Aerial Vehicle ◽  
Optimization Algorithm ◽  
Mobile Technologies ◽  
Complex Environments ◽  
Real Time Processing ◽  
Time Processing ◽  
Aerial Vehicle ◽  
And Storage ◽  
Mobile Condition

With the advance of mobile technologies, mobile devices such as unmanned aerial vehicle (UAV) become more important in video surveillance. By applying mobile person re-identification (re-id), mobile devices can monitor pedestrians in the transportation system from complex environments. Since the computing and storage resources of mobile devices are limited, traditional person re-id methods are not appropriate for mobile condition. Besides, mobile person re-id task also requires real-time processing. In this paper, we propose a novel hashing method: online discrete anchor graph hashing (ODAGH) for mobile person re-id. ODAGH integrates the advantages of online learning and hashing technology. In ODAGH, we propose an online discrete optimization algorithm to improve the efficiency of anchor graph learning in the online scenario. Experimental results demonstrate the superiority of ODAGH in terms of both effect and efficiency.

scholarly journals Trajectory planning of quadrotor using sliding mode control with extended state observer

2020 ◽  
Vol 53 (7-8) ◽  
pp. 1300-1308
Author(s):  
Jun Xiao
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Trajectory Planning ◽  
Attitude Control ◽  
Sliding Mode ◽  
State Observer ◽  
Control Model ◽  
Extended State Observer ◽  
Extended State ◽  
Inner Model ◽  
Aerial Vehicle

This paper presents the trajectory planning of an under-actuated quadcopter unmanned aerial vehicle. To control the complete structure of the rotorcraft, the main model is divided into two sub-models, namely inner model and external model. The inner model is for the attitude control model controlled by the sliding mode controller and the outer model is altitude control model governed by the extended state observer. The quadrotor unmanned aerial vehicle is a type of multivariable, multi-degree-of-freedom and nonlinear in nature. Planning the trajectory of the unmanned aerial vehicle and stabilizing its flight are complex tasks because of its ability to maneuver quickly. Due to these stated issues, the tuning of this type of dynamic system is a difficult task. This paper deals with these issues by designing the aforementioned dual controller scheme. In addition, the effectiveness of the proposed controller is apparent in simulations performed in MATLAB, Simulink 2016. The designed controller shows better results and robustness than traditional controllers do.

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