Multi-UCAV Air Combat Task Assignment under Uncertain Information Environment

2014 ◽  
Vol 494-495 ◽  
pp. 1098-1101 ◽  
Author(s):  
Xia Chen ◽  
De Hui Wang
Keyword(s):  
Particle Swarm Optimization Algorithm ◽  
Task Assignment ◽  
Information Environment ◽  
Uncertain Information ◽  
Analysis Method ◽  
Discrete Particle Swarm Optimization ◽  
Allocation Model ◽  
Air Combat ◽  
Task Assignment Problem ◽  
Multi Uav

For UAV air combat task assignment problem, this paper presents an analysis method. Firstly, we analyzes the unmanned combat situation, establish the UAV air combat situation advantage function and interval information combat task allocation model. And then put forward multi-UAV air combat decision method of the discrete particle swarm optimization algorithm based on interval number sequence. Finally, we carry on the simulation, the simulation results show that the algorithm can effectively and reasonably solve the problem of multi-UAV air combat decision.

scholarly journals Task Assignment for Multi-UAV under Severe Uncertainty by Using Stochastic Multicriteria Acceptability Analysis

2015 ◽  
Vol 2015 ◽  
pp. 1-10 ◽  
Author(s):  
Xiaoxuan Hu ◽  
Jing Cheng ◽  
He Luo
Keyword(s):  
Unmanned Aerial Vehicles ◽  
Task Assignment ◽  
Uncertain Information ◽  
Simulation Experiments ◽  
Aerial Vehicles ◽  
Multiple Unmanned Aerial Vehicles ◽  
Severe Uncertainty ◽  
Task Assignment Problem ◽  
Multi Uav ◽  
Assignment Approach

This paper considers a task assignment problem for multiple unmanned aerial vehicles (UAVs). The UAVs are set to perform attack tasks on a collection of ground targets in a severe uncertain environment. The UAVs have different attack capabilities and are located at different positions. Each UAV should be assigned an attack task before the mission starts. Due to uncertain information, many criteria values essential to task assignment were random or fuzzy, and the weights of criteria were not precisely known. In this study, a novel task assignment approach based on stochastic Multicriteria acceptability analysis (SMAA) method was proposed to address this problem. The uncertainties in the criteria were analyzed, and a task assignment procedure was designed. The results of simulation experiments show that the proposed approach is useful for finding a satisfactory assignment under severe uncertain circumstances.

scholarly journals Multi-UAV Rapid-Assessment Task-Assignment Problem in a Post-Earthquake Scenario

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 74542-74557 ◽  
Author(s):  
Moning Zhu ◽  
Xiaoxia Du ◽  
Xuehua Zhang ◽  
He Luo ◽  
Guoqiang Wang
Keyword(s):  
Assignment Problem ◽  
Rapid Assessment ◽  
Task Assignment ◽  
Earthquake Scenario ◽  
Assessment Task ◽  
Task Assignment Problem ◽  
Multi Uav

scholarly journals Hierarchical Task Assignment Strategy for Heterogeneous Multi-UAV System in Large-Scale Search and Rescue Scenarios

2021 ◽  
Vol 2021 ◽  
pp. 1-19
Author(s):  
Jie Chen ◽  
Kai Xiao ◽  
Kai You ◽  
Xianguo Qing ◽  
Fang Ye ◽  
...  
Keyword(s):  
Large Scale ◽  
Cluster Head ◽  
Task Assignment ◽  
Search And Rescue ◽  
Small Scale ◽  
Assignment Strategy ◽  
Negotiation Mechanism ◽  
Decoupling Algorithm ◽  
Task Assignment Problem ◽  
Multi Uav

For the large-scale search and rescue (S&R) scenarios, the centralized and distributed multi-UAV multitask assignment algorithms for multi-UAV systems have the problems of heavy computational load and massive communication burden, which make it hard to guarantee the effectiveness and convergence speed of their task assignment results. To address this issue, this paper proposes a hierarchical task assignment strategy. Firstly, a model decoupling algorithm based on density clustering and negotiation mechanism is raised to decompose the large-scale task assignment problem into several nonintersection and complete small-scale task assignment problems, which effectively reduces the required computational amount and communication cost. Then, a cluster head selection method based on multiattribute decision is put forward to select the cluster head for each UAV team. These cluster heads will communicate with the central control station about the latest assignment information to guarantee the completion of S&R mission. At last, considering that a few targets cannot be effectively allocated due to UAVs’ limited and unbalanced resources, an auction-based task sharing scheme among UAV teams is presented to guarantee the mission coverage of the multi-UAV system. Simulation results and analyses comprehensively verify the feasibility and effectiveness of the proposed hierarchical task assignment strategy in large-scale S&R scenarios with dispersed clustering targets.

Multi-UCAV Task Allocation Based on SMAA in Uncertain Information Environment

2013 ◽  
Vol 380-384 ◽  
pp. 1180-1184
Author(s):  
Xia Chen ◽  
Xiao Ming Wei ◽  
Yong Xin Hu
Keyword(s):  
Task Allocation ◽  
Information Environment ◽  
Uncertain Information ◽  
Uncertain Environment ◽  
Air Combat

According to the problem of multi-UCAV air-combat task allocation in uncertain environment, first consider the uncertainty elementsin the air-combat, the model of air-combat situation based on interval information is built, and combinat air combat situation predominance and attack gains, Finally, the model for task allocation of Multi-UCAV cooperative combat is built. Then Analysy to solve the problem used SMAA, the results show the feasibility and effectiveness of the method.

scholarly journals On-Demanding Information Acquisition in Multi-UAV-Assisted Sensor Network: A Satisfaction-Driven Perspective

2021 ◽  
Vol 2021 ◽  
pp. 1-14
Author(s):  
Hua Yang ◽  
Jungang Yang ◽  
Wendong Zhao ◽  
Cuntao Liu
Keyword(s):  
Energy Consumption ◽  
User Satisfaction ◽  
Assignment Problem ◽  
Information Acquisition ◽  
Time Window ◽  
Task Assignment ◽  
Total Energy Consumption ◽  
Time Window Constraints ◽  
Task Assignment Problem ◽  
Multi Uav

When multiple heterogeneous unmanned aerial vehicles (UAVs) provide service for multiple users in sensor networks, users’ diverse priorities and corresponding priority-related satisfaction are rarely concerned in traditional task assignment algorithms. A priority-driven user satisfaction model is proposed, in which a piecewise function considering soft time window and users’ different priority levels is designed to describe the relationship between user priority and user satisfaction. On this basis, the multi-UAV task assignment problem is formulated as a combinatorial optimization problem with multiple constraints, where the objective is maximizing the priority-weighted satisfaction of users while minimizing the total energy consumption of UAVs. A multipopulation-based cooperation genetic algorithm (MPCGA) by adapting the idea of “exploration-exploitation” into traditional genetic algorithms (GAs) is proposed, which can solve the task assignment problem in polynomial time. Simulation results show that compared with the algorithm without considering users’ priority-based satisfaction, users’ weighted satisfaction can be improved by about 47% based on our algorithm in situations where users’ information acquisition is tight time-window constraints. In comparison, UAVs’ energy consumption only increased by about 6%. Besides, compared with traditional GA, our proposed algorithm can also improve users’ weighted satisfaction by about 5% with almost the same energy consumption of UAVs.

On-Orbit Servicing Task Allocation for Spacecrafts Using Discrete Particle Swarm Optimization Algorithm

2011 ◽  
Vol 268-270 ◽  
pp. 574-580
Author(s):  
Qi Xin Zhang ◽  
Fu Chun Sun ◽  
Wen Ye ◽  
Jie Chen
Keyword(s):  
Particle Swarm Optimization ◽  
Task Allocation ◽  
Particle Swarm Optimization Algorithm ◽  
Particle Swarm ◽  
Critical Index ◽  
Discrete Particle Swarm Optimization ◽  
Allocation Model ◽  
Swarm Optimization ◽  
Discrete Particle ◽  
Update Strategy

The on-orbit servicing task allocation is very important to improve the cooperative work ratio of the on-orbit servicing spacecraft. A discrete particle swarm optimization (DPSO) algorithm is put forward for on-orbit servicing spacecraft cooperative task allocation problems. A new code of particles and new update strategy for the position and speed of particles are applied. By analyzing the critical index factors which contain target spacecraft value, servicing spacecraft attrition and energy-time consumption, on-orbit spacecraft task allocation model is formulated. The simulation results show that the DPSO algorithm has fast convergence, optimization capability, and can solve the on-orbit servicing spacecraft cooperative task allocation effectively.

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