Multi-UAV Distributed Collaborative Coverage for Target Search Using Heuristic Strategy

2021 ◽  
Vol 01 (01) ◽  
pp. 2150002
Author(s):  
Kai Zhu ◽  
Bin Han ◽  
Tao Zhang
Keyword(s):  
Parallel Search ◽  
Target Movement ◽  
Target Search ◽  
Detection Range ◽  
Evaluation Functions ◽  
Sudden Failure ◽  
State Transfer ◽  
Heuristic Strategy ◽  
Simulation Results ◽  
Multi Uav

Collaborative coverage for target search using a group of unmanned aerial vehicles (UAVs) has received increasing attention in recent years. However, the design of distributed control strategy and coordination mechanisms remains a challenge. This paper presents a distributed and online heuristic strategy to solve the problem of multi-UAV collaborative coverage. As a basis, each UAV maintains a probability grid map in the form of a locally stored matrix, without shared memory. Then we design two evaluation functions and related technical strategies to enable UAVs to make state transfer or area transfer decisions in an online self-organizing way. The simulation results show that the algorithm integrates geometric features such as parallel search and internal spiral search, and is not interfered by factors such as sudden failure of UAVs, changes in detection range, and target movement. Compared with other commonly used methods for target search, our strategy has high search efficiency, good robustness, and fault tolerance.

scholarly journals RFID Antenna for UHF Band

2019 ◽  
Vol 12 (2) ◽  
pp. 28-32
Author(s):  
Nicolae Crișan
Keyword(s):  
North America ◽  
Circular Polarization ◽  
Rfid Tags ◽  
Metallic Surfaces ◽  
Detection Range ◽  
Simulation And Optimization ◽  
Sensing Range ◽  
Simulation Results ◽  
Radio Band ◽  
Uhf Band

Abstract This paper presents a method to increase the detection range for RFID readers in the UHF radio band. The design is following especially the ISO 18000-6C standardization demands for the UHF band, operating from 865 to 868 MHz in Europe and from 902 to 928 MHz in North America. These regulations are allowing the RFID tags to operate near the metallic surfaces and in a wider range than its counterparts at lower frequencies. The paper highlights the advantages offered by the array antenna, especially by the beamforming to increase the reader surveillance zone. The paper describes some additional techniques that are allowing the usage of the circular polarization to increase the reader sensing range and to improuve detection. The design starts with simulation and optimization using HFSS and ends with the measurements that validate the simulation results.

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 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.

scholarly journals Efficient blind adaptive Karhunen–Loéve transform via parallel search

2018 ◽  
Vol 14 (6) ◽  
pp. 155014771878237
Author(s):  
Wenbiao Tian ◽  
Guosheng Rui ◽  
Daoguang Dong ◽  
Jian Kang
Keyword(s):  
Numerical Simulation ◽  
Data Compression ◽  
Search Strategy ◽  
Original Data ◽  
Parallel Search ◽  
Efficient Search ◽  
Blind Adaptive ◽  
Simulation Results ◽  
Karhunen Loeve Transform ◽  
Minimal Information

This article introduces a new algorithm that constructs an efficient search strategy, called parallel search, for blind adaptive Karhunen–Loéve transform. Unlike anterior Karhunen–Loéve transform, the proposed algorithm converges quickly by searching for solutions in different directions simultaneously. Moreover, the process is “blind,” which means that minimal information about the original data is used. The new algorithm also avoids repeating the Karhunen–Loéve transform basis learning step in data compression applications. Numerical simulation results verify the validity of the theory and illustrate the capability of the proposed algorithm.

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.

scholarly journals Cooperative Solution of Multi-UAV Rendezvous Problem with Network Restrictions

2015 ◽  
Vol 2015 ◽  
pp. 1-14 ◽  
Author(s):  
Qingjie Zhang ◽  
Jianwu Tao ◽  
Fei Yu ◽  
Yingzhen Li ◽  
Hongchang Sun ◽  
...  
Keyword(s):  
Game Theory ◽  
Cooperative Game ◽  
Cooperative Game Theory ◽  
Parameter Method ◽  
Redundant Information ◽  
Cooperative Solution ◽  
Rendezvous Problem ◽  
Simulation Results ◽  
Coordination Function ◽  
Multi Uav

By considering the complex networks, the cooperative game based optimal consensus (CGOC) algorithm is proposed to solve the multi-UAV rendezvous problem in the mission area. Firstly, the mathematical description of the rendezvous problem is established, and the solving framework is provided based on the coordination variables and coordination function. It can decrease the transmission of the redundant information and reduce the influence of the limited network on the task. Secondly, the CGOC algorithm is presented for the UAVs in distributed cooperative manner, which can minimize the overall cost of the multi-UAV system. The CGOC control problem and the corresponding solving protocol are given by using the cooperative game theory and sensitivity parameter method. Then, the CGOC method of multi-UAV rendezvous problem is proposed, which focuses on the trajectory control of the platform rather than the path planning. Simulation results are given to demonstrate the effectiveness of the proposed CGOC method under complex network conditions and the benefit on the overall optimality and dynamic response.

Cooperative Area Coverage Reconnaissance Method for Multi-UAV System

2011 ◽  
Vol 383-390 ◽  
pp. 4141-4146
Author(s):  
Guo Qing Long ◽  
Xiao Ping Zhu
Keyword(s):  
Clustering Algorithm ◽  
Area Coverage ◽  
Space Distribution ◽  
Task Sequence ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering ◽  
Simulation Results ◽  
Membership Matrix ◽  
Multi Uav

Aiming to find a solution, the method of cooperative area coverage reconnaissance for Multi-UAV system is proposed by combining centralized preplanning with distributed partial online replanning. In the preplanning, grid disintegration is applied to divide the area to be reconnoitered into task sequence of nodes and fuzzy C-means clustering algorithm is applied to conduct space distribution of task nodes; the online partial replanning is that the left UAVs automatically complete the unfinished task of the failed UAV, using the membership matrix got by clustering algorithm as a unified standard, which ensures that so long as one UAV does not fail, the reconnaissance task can be normally carried on. The simulation results show that this method, simple yet with a high robustness, can effectively solve the problem of multi-UAV cooperative area coverage reconnaissance.

Algorithm of Marriage in Honey Bees Optimization Coperate with Linear Method

2013 ◽  
Vol 871 ◽  
pp. 330-337
Author(s):  
Chen Guang Yang ◽  
Qiao Ge Liu
Keyword(s):  
Honey Bees ◽  
Linear Method ◽  
Local Characteristic ◽  
Evaluation Functions ◽  
Markov Chain Theory ◽  
Computation Process ◽  
Public Evaluation ◽  
Convergence Performance ◽  
Chain Theory ◽  
Simulation Results

Marriage in Honey Bees Optimization (MBO) is a new swarm-intelligence method, but it has the shortcomings of low speed and complex computation process. By changing the structure of MBO and utilizing a linear method to perform the local characteristic, we propose a new optimization algorithm. The global convergence characteristic of the proposed algorithm is proved by using the Markov Chain theory. And then some simulations are done on Traveling Salesman Problem (TSP) and several public evaluation functions. By comparing the proposed algorithm with MBO and Genetic Algorithm, simulation results show that the proposed algorithm has better convergence performance.

scholarly journals Multi-UAVs Cooperative Localization Algorithms with Communication Constraints

2017 ◽  
Vol 2017 ◽  
pp. 1-8 ◽  
Author(s):  
Xiaowei Fu ◽  
Haiyang Bi ◽  
Xiaoguang Gao
Keyword(s):  
Packet Loss ◽  
Estimation Method ◽  
Cooperative Localization ◽  
Bernoulli Random Variables ◽  
Localization Algorithms ◽  
One Step ◽  
Centralized Algorithm ◽  
Simulation Results ◽  
Multi Uav ◽  
Prediction Strategy

Communication is the basis of multi-UAVs cooperative localization. There will be some communication delay and packet loss when one UAV communicates with others, and these communication restrictions may have negative influences on multi-UAV cooperative localization. In this paper, the communication among UAVs is described as Bernoulli random variables, and two kinds of cooperative localization algorithms are proposed. One is centralized algorithm, where a kind of one-step prediction strategy is designed. The other is distributed algorithm, where a kind of prediction-compensation strategy is proposed and weighted expectation state estimation method is designed. Simulation results show the effectiveness of the proposed algorithms.

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