Multi-UAV Cooperative Task Planning for Border Patrol based on Hierarchical Optimization

2021 ◽  
Author(s):  
Hai-shi Liu ◽  
Yu-xuan Sun ◽  
Nan Pan ◽  
Qi-yong Chen ◽  
Xiao-jue Guo ◽  
...  
Keyword(s):  
Chaos Theory ◽  
Hierarchical Optimization ◽  
Border Patrol ◽  
Complex Environments ◽  
Environmental Model ◽  
Other Information ◽  
Aerial Vehicle ◽  
Scene Information ◽  
Simulation Results ◽  
Multi Uav

In order to improve the patrol efficiency of border patrol drones, based on unmanned aerial vehicle (UAV) border patrol missions in multiple complex environments, this article proposes a whale algorithm based on chaos theory to plan patrol missions for multiple drones. First, according to the terrain the corresponding environmental model is established for the topography and then solved in layers to obtain the number of drones and other information that each base needs to send to the patrol area. Further, the use of drones with cameras and other detection equipment to patrol the scene information and images extract and transfer to the terminal in real time, and further detect suspicious persons and vehicles on the screen. The final simulation results show that the proposed scheme can be effectively applied to the planning of multi-UAV coordinated missions for border patrol.

scholarly journals Towards Flocking Navigation and Obstacle Avoidance for Multi-UAV Systems through Hierarchical Weighting Vicsek Model

Aerospace ◽  
2021 ◽  
Vol 8 (10) ◽  
pp. 286
Author(s):  
Xingyu Liu ◽  
Chao Yan ◽  
Han Zhou ◽  
Yuan Chang ◽  
Xiaojia Xiang ◽  
...  
Keyword(s):  
Obstacle Avoidance ◽  
High Performance ◽  
Local Information ◽  
Convergence Time ◽  
Complex Environments ◽  
System Safety ◽  
Vicsek Model ◽  
Aerial Vehicle ◽  
Weighting Mechanism ◽  
Multi Uav

Flocking navigation and obstacle avoidance in complex environments remain challenging for multiple unmanned aerial vehicle (multi-UAV) systems, especially when only one UAV (termed as information UAV) knows the predetermined path and the communication range is limited. To this end, we propose a hierarchical weighting Vicsek model (HWVEM). In this model, a hierarchical weighting mechanism and an obstacle avoidance mechanism are designed. Based on the hierarchical weighting mechanism, all the UAVs are divided into different layers, and assigned with different weights according to the layer to which they belong. The purpose is to align the rest of UAVs with the information UAV more efficiently. Subsequently, the obstacle avoidance mechanism that utilizes only the local information is developed to ensure the system safety in an environment filled with obstacles differing in size and shape. A series of simulations have been conducted to demonstrate the high performance of HWVEM in terms of convergence time, success rate, and safety.

scholarly journals Effects of Motion Compensation Residual Error and Polarization Distortion on UAV-Borne PolInSAR

2021 ◽  
Vol 13 (4) ◽  
pp. 618
Author(s):  
Zexin Lv ◽  
Fangfang Li ◽  
Xiaolan Qiu ◽  
Chibiao Ding
Keyword(s):  
Motion Compensation ◽  
Residual Error ◽  
Synthetic Aperture ◽  
Interferometric Synthetic Aperture Radar ◽  
Practical Application ◽  
Aerial Vehicle ◽  
Application Potential ◽  
Large Motion ◽  
Simulation Results ◽  
Interferometric Sar

Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) can improve interferometric coherence and phase quality, which has good application potential. With the development of the Mini-SAR system, Unmanned Aerial Vehicle borne (UAV-borne) PolInSAR systems became a reality. However, UAV-borne PolInSAR is easily affected by air currents and other factors, which may cause large motion errors and polarization distortion inevitably exists. However, there are few pieces of research which are about motion compensation residual error (MCRE) and polarization distortion effects on PolInSAR. Though the effects of MCRE on Interferometric SAR (InSAR) and polarization distortion on PolInSAR were studied, respectively, these two parts are independently modeled and analyzed. In this paper, a model that simultaneously considers the effects of these two kinds of errors is proposed, and simulation results are given to validate the model. Then, a quantitative analysis based on a real Quadcopter UAV PolInSAR system is performed according to the model, which is valuable for system design and practical application of the UAV-borne PolInSAR system.

Study on Micro-Fracture Chaotic Evolution under External Loading Rock

2013 ◽  
Vol 813 ◽  
pp. 355-358 ◽  
Author(s):  
Ting Ting Wang ◽  
Wan Chun Zhao ◽  
Yuan Hong Liu ◽  
Li Yang ◽  
Hong Yu Gao
Keyword(s):  
Finite Element ◽  
Chaos Theory ◽  
Formation Process ◽  
Theoretical Calculations ◽  
Growth Behavior ◽  
External Loading ◽  
Software Simulation ◽  
Finite Element Software ◽  
Fracture Formation ◽  
Simulation Results

In order to accurately describe the growth behavior of the micro-fracture under the action of the rock external load, this paper proposes the use of chaos theory to describe the fracture formation process, explains the chaotic characteristics of the fracture from the perspective of the growth of micro-fracture, the number of growth and fracture formation morphology, respectively. Selecting the practical block of an oilfield, the theoretical calculation and finite element software simulation results show that, theoretical calculations are accurate and reliable.

scholarly journals Dynamic Routing and Coordination of Cluster for Unmanned Aerial Vehicle (UAV) Swarms

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Ali Abbas ◽  
Bhawani Shankar Chowdhry ◽  
Muhammad Saqib ◽  
Vishal Dattana
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Efficient Solution ◽  
High Mobility ◽  
Combinatorial Problem ◽  
Communication Graph ◽  
Frequent Change ◽  
Swarm Optimization ◽  
Wide Range ◽  
Aerial Vehicle ◽  
Simulation Results

The flying networks provide an efficient solution for a wide range of military and commercial purposes. The demand for portable and flexible communication is directed towards a quick growth in interaction among unmanned aerial vehicles (UAVs). Due to the frequent change in topology and high mobility of vehicles, routing and coordination becomes a challenging task. To maximize the throughput of the network, this study addresses the UAV swarm’s problems related to the coordination and routing and defines the proposed solution to solve these issues. For this, a network is assumed which contains an equal number of dynamic vehicles. It also presents the communication graph concept of UAVs and designs a fixed-wing UAV model to improve the efficiency of the network in terms of throughput. Furthermore, the proposed algorithm based on Cauchy particle swarm optimization (CPSO) aims towards the better performance of UAV swarms and aims to solve the combinatorial problem. The simulation results show and confirm the performance of the proposed algorithm.

scholarly journals PERANCANGAN AUTOPILOT LATERAL-DIREKSIONAL PESAWAT NIRAWAK LSU-05 (THE DESIGN OF THE LATERAL-DIRECTIONAL AUTOPILOT FOR THE LSU-05 UNMANNED AERIAL VEHICLE)

2018 ◽  
Vol 15 (2) ◽  
pp. 93 ◽  
Author(s):  
Muhammad Fajar ◽  
Ony Arifianto
Keyword(s):  
State Space ◽  
Linear Model ◽  
Unmanned Aerial Vehicle ◽  
Pid Controller ◽  
Settling Time ◽  
Proportional Integral Derivative ◽  
Proportional Integral ◽  
Directional Motion ◽  
Aerial Vehicle ◽  
Simulation Results

The autopilot on the aircraft is developed based on the mode of motion of the aircraft i.e. longitudinal and lateral-directional motion. In this paper, an autopilot is designed in lateral-directional mode for LSU-05 aircraft. The autopilot is designed at a range of aircraft operating speeds of 15 m/s, 20 m/s, 25 m/s, and 30 m/s at 1000 m altitude. Designed autopilots are Roll Attitude Hold, Heading Hold and Waypoint Following. Autopilot is designed based on linear model in the form of state-space. The controller used is a Proportional-Integral-Derivative (PID) controller. Simulation results show the value of overshoot / undershoot does not exceed 5% and settling time is less than 30 second if given step command. Abstrak Autopilot pada pesawat dikembangkan berdasarkan pada modus gerak pesawat yaitu modus gerak longitudinal dan lateral-directional. Pada makalah ini, dirancang autopilot pada modus gerak lateral-directional untuk pesawat LSU-05. Autopilot dirancang pada range kecepatan operasi pesawat yaitu 15 m/dtk, 20 m/dtk, 25 m/dtk, dan 30 m/dtk dengan ketinggian 1000 m. Autopilot yang dirancang adalah Roll Attitude Hold, Heading Hold dan Waypoint Following. Autopilot dirancang berdasarkan model linier dalam bentuk state-space. Pengendali yang digunakan adalah pengendali Proportional-Integral-Derivative (PID). Hasil simulasi menunjukan nilai overshoot/undershoot tidak melebihi 5% dan settling time kurang dari 30 detik jika diberikan perintah step.

scholarly journals Information Distribution in Multi-Robot Systems: Utility-Based Evaluation Model

Sensors ◽  
2020 ◽  
Vol 20 (3) ◽  
pp. 710 ◽  
Author(s):  
Michał Barciś ◽  
Agata Barciś ◽  
Hermann Hellwagner
Keyword(s):  
Evaluation Model ◽  
Proof Of Concept ◽  
Information Distribution ◽  
Unified Framework ◽  
Robot Operating System ◽  
Robot Systems ◽  
System 2 ◽  
Aerial Vehicle ◽  
Multi Uav ◽  
Multi Robot

This work addresses the problem of information distribution in multi-robot systems, with an emphasis on multi-UAV (unmanned aerial vehicle) applications. We present an analytical model that helps evaluate and compare different information distribution schemes in a robotic mission. It serves as a unified framework to represent the usefulness (utility) of each message exchanged by the robots. It can be used either on its own in order to assess the information distribution efficacy or as a building block of solutions aimed at optimizing information distribution. Moreover, we present multiple examples of instantiating the model for specific missions. They illustrate various approaches to defining the utility of different information types. Finally, we introduce a proof of concept showing the applicability of the model in a robotic system by implementing it in Robot Operating System 2 (ROS 2) and performing a simple simulated mission using a network emulator. We believe the introduced model can serve as a basis for further research on generic solutions for assessing or optimizing information distribution.

Multi-UAV Specification and Control with a Single Pilot-in-the-Loop

2020 ◽  
Vol 08 (04) ◽  
pp. 269-277
Author(s):  
Patricio Moreno ◽  
Santiago Esteva ◽  
Ignacio Mas ◽  
Juan I. Giribet
Keyword(s):  
Remote Control ◽  
Unmanned Aerial Vehicles ◽  
Field Experiments ◽  
Aerial Vehicles ◽  
Simulated Environment ◽  
Aerial Vehicle ◽  
Space Formulation ◽  
Trajectory Following ◽  
And Control ◽  
Multi Uav

This work presents a multi-unmanned aerial vehicle formation implementing a trajectory-following controller based on the cluster-space robot coordination method. The controller is augmented with a feed-forward input from a control station operator. This teleoperation input is generated by means of a remote control, as a simple way of modifying the trajectory or taking over control of the formation during flight. The cluster-space formulation presents a simple specification of the system’s motion and, in this work, the operator benefits from this capability to easily evade obstacles by means of controlling the cluster parameters in real time. The proposed augmented controller is tested in a simulated environment first, and then deployed for outdoor field experiments. Results are shown in different scenarios using a cluster of three autonomous unmanned aerial vehicles.

Elastic Formation Keeping Control of Unmanned Aerial Vehicle Adapting to Flight Speed

2013 ◽  
Vol 367 ◽  
pp. 411-416 ◽  
Author(s):  
Guang Yan Xu ◽  
Yi Bo Shi
Keyword(s):  
Unmanned Aerial Vehicle ◽  
Relative Position ◽  
State Feedback ◽  
Feedback Controller ◽  
Flight Speed ◽  
Dynamic Equations ◽  
Aerial Vehicle ◽  
Distance Vector ◽  
Simulation Results ◽  
Formation Keeping

For an Unmanned Aerial Vehicle (UAV) formation in leader-follower mode, considering the relative position relationship between neighbor vehicles in the formation, an elastic distance vector is proposed. The dynamic equations of a flight speed adaptive UAV formation are established using the elastic distance vector we proposed. The state feedback controller is designed. Simulation results show that the controller can be used to control the follower vehicles to follow the leader vehicle maneuvering effectively and keep the desired formation well, most importantly, the relative distance between neighbor vehicles in the formation is adapted to the changes of flight speed.

scholarly journals A Novel Searching Method Using Reinforcement Learning Scheme for Multi-UAVs in Unknown Environments

2019 ◽  
Vol 9 (22) ◽  
pp. 4964 ◽  
Author(s):  
Yue ◽  
Guan ◽  
Wang
Keyword(s):  
Reinforcement Learning ◽  
Prior Information ◽  
Search Task ◽  
Efficiency Function ◽  
Awareness Information ◽  
Simulation Results ◽  
Searching Method ◽  
Sea Area ◽  
Sensor Detection ◽  
Multi Uav

In this paper, the important topic of cooperative searches for multi-dynamic targets in unknown sea areas by unmanned aerial vehicles (UAVs) is studied based on a reinforcement learning (RL) algorithm. A novel multi-UAV sea area search map is established, in which models of the environment, UAV dynamics, target dynamics, and sensor detection are involved. Then, the search map is updated and extended using the concept of the territory awareness information map. Finally, according to the search efficiency function, a reward and punishment function is designed, and an RL method is used to generate a multi-UAV cooperative search path online. The simulation results show that the proposed algorithm could effectively perform the search task in the sea area with no prior information.

Decentralized Control Method of Multi-UAVs Arriving at the Same Time under the Influence of Wind

2013 ◽  
Vol 336-338 ◽  
pp. 595-598
Author(s):  
Xia Chen ◽  
Chong Zhang
Keyword(s):  
Control Problem ◽  
Decentralized Control ◽  
Control Method ◽  
Starting Point ◽  
Wind Simulation ◽  
Simulation Results ◽  
Multi Uav

Decentralized control method of multi-uav arriving at the same time is a typical control problem. This paper considers the above problem and presents a decentralized control method. Considering the dynamics and uncertainty of the battlefront, and the feature of the uav, according to the different starting point, flying orientation, and distance, established the algorithm model of the velocity and direction of uav under the influence of wind, presenting a decentralize control method of multi-uav arriving at the same time under the influence of wind. Simulation results are presented to demonstrate the effectiveness, robustness, flexibility of the approach.

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