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A summary of the development of cooperative and intelligent technology for multi-UAV systems

A summary of the development of cooperative and intelligent ...

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2019 IEEE International Conference on Unmanned systems and Artificial Intelligence, ICUSAI 2019

作者： Zhou, Huan Su, Qian Fu, Wenxing Xu, Cheng Zheng, Meiyun Yang, Jingguang Aeronautical Engineering College Air Force Engineering University Xi'an China School of Astronautics Northwest Polytechnical University Xi'an China Unmanned System Research Institute Northwest Polytechnical University Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China School of Marine Science and Technology Northwest Polytechnical University Xi'an China Aviation Maintenance Sergeant School of Air Force Engineering University Xinyang China

ISBN: (纸本)9781728158594

In the process of formation cooperative autonomous flight and mission execution, multi-UAV systems have the characteristics of large disturbance, strong coupling of multi variables, high degree of uncertainty and complex cooperative factors, so there are many difficulties in the design of cooperative and intelligent control system. How to effectively develop the cooperative and intelligent technology of multi-UAV systems has become an urgent problem in the field of unmanned system and artificial intelligence. This paper first introduces the key technologies involved in UAV system at present, and then analyzes the challenges faced by the development of UAV system. Finally, it focuses on the development trend of multi-UAV systems cooperation and intelligent technology in the future. The research results have strong theoretical guidance significance for the cooperation and intelligent development of multi-UAV systems in China. © 2019 IEEE.

关键词： Flight control systems

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SAR Image Registration Based on Feature Points Using Improved CSP-DenseNet

SAR Image Registration Based on Feature Points Using Improve...

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Pattern Recognition and Artificial Intelligence (PRAI), International Conference on

作者： Ziwei Wang Yanjiao Yang Guangzhou Qu Qingxi Chi Beijing Electro-Mechanical Engineering Institute Beijing China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

Synthetic aperture radar (SAR) image registration is widely used in integrated navigation system with development of guidance system in sensors and other applications. However, there exists some difficulty because of the quality and imaginary principle of SAR images. In this article, a brand-new method based on feature points using improved CSP-DenseNet is proposed to solve the problems of SAR image registration with weak and noisy texture. Deep features of interest points in SAR images are extracted using the proposed network from the crops of search image and template image respectively. The method has an advantage of preserving abundant feature information in SAR images under the influence of insufficient image information and noise of SAR images. The CSP-DenseNet architecture has a cross-stage construction optimizing fused by CSP-Net and DenseNet to extract matching features. The network is partially connected in specific convolutional layers for feature reusing and computation resources saving. Then, Brute Force Matcher and RANSAC voting are successively applied for a larger number of matching pairs and high-precise matching vertexes. Experimental results on various SAR image matching methods show that the proposed method provides better performance than other approaches compared.

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An autonomous path planning method considering terrain aided navigation constraints

An autonomous path planning method considering terrain aided...

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Chinese Automation Congress (CAC)

作者： Min Jiang Cheng Xu Hua Ji Yuqi Wang Beijing Electro-Mechanical Engineering Institute Bejing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Bejing China

In order to solve the autonomous path planning problem with terrain aided navigation constraints, a navigation-first path planning method was adopted, that is, the distribution of terrain matching regions and the drift of navigation errors were given priority, and the path planning problem was transformed into the shortest path problem of single source directed graph to determine the nodes on the path. Secondly, the path planning between adjacent nodes is transformed into a path planning problem with initial direction constraint and terminal direction freedom/constraint, and the lateral path is smoothed. Finally, for the local path passing through the no-fly zone, the obstacle avoidance path planning with initial and terminal direction constraints is carried out based on convex optimization method. The simulation results show that the autonomous path planning method considering terrain aided navigation constraints can plan the shortest flight path under the constraints of navigation accuracy, maneuverability and no-fly zone.

关键词： Smoothing methods Navigation Trajectory planning Simulation Directed graphs Turning Path planning

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A strategy of multi-UAV cooperative path planning based on CCPSO

A strategy of multi-UAV cooperative path planning based on C...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Yuanna Liu Hao Lu dept. School of Electronics and Information Northwestern Polytechnical University Xi’an China dept. Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728137933

Multi-UAV cooperative formation flying has significant advantages in broadening the scope of UAV operations and improving combat effectiveness. How to realize the cooperative path planning of multi-UAV is an open issue. In order to solve the search performance degradation as dimension increases, a strategy of multi-UAV cooperative path planning based on Cooperative Coevolution Particle Swarm Optimization (CCPSO) is proposed in this paper. Firstly, the initial Dubins path is generated for each UAV in the formation, of which the longest one is selected as the reference path. Intermediate waypoints are designed to modify the initial paths to avoid collisions with obstacles. Then, CCPSO algorithm is applied to optimize path parameters and adjust the path length to be equal to the reference path to ensure time coordination. Collision avoidance between UAVs is achieved in the collaborative evaluation phase. Finally, an formation rendezvous example and comparison with CCGA are given to explain the validity and excellent search ability of the proposed method.

关键词： Path planning Optimization Particle swarm optimization Safety Unmanned aerial vehicles Collision avoidance Planning

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Motion primitives-based and Two-phase Motion Planning for Fixed-wing UAV

Motion primitives-based and Two-phase Motion Planning for Fi...

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International Conference on control, Automation, Robotics and Vision (ICARCV)

作者： Zheng Tan Yang Lyu Hanchen Lu Quan Pan Faculty of Automation Northwestern Polytechnical University Xi'an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing China

ISBN: (纸本)9781665476881

We present an efficient two-phase approach to motion planning for fixed-wing Unmanned Aerial Vehicles (UAV) navigating in complex 3D air slalom environments. Firstly, in discrete 3D workspace, a global planner computer a obstacle-free path roughly which satisfies the kinematic constraints of the UAV. Given a coarse global path, a local planner generate a Dubins curve with collision avoidance based on the UAS's perception constraints, dynamic constraints and the collision perception information received. We also introduce a method of decoupling the horizontal and vertical motion directions of the fixed-wing UAV, realizing the 2D Dubins curve planning in 3D workspace, along with precomputed sets of motion primitives derived from the vehicle dynamics model in order to achieve high efficiency. Finally, the feasibility of two-phase 3D motion planning in appropriate FOV is experimentally demonstrated.

关键词： Solid modeling Three-dimensional displays Navigation Dynamics Organizations Kinematics Autonomous aerial vehicles

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Model-free Based Reinforcement Learning control Strategy of Aircraft Attitude systems

Model-free Based Reinforcement Learning Control Strategy of ...

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Chinese Automation Congress (CAC)

作者： Dingcui Huang Jiangping Hu Zhinan Peng Bo Chen Mingrui Hao Bijoy Kumar Ghosh School of Automation Engineering University of Electronic Science and Technology of China Chengdu China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China Texas Tech University Lubbock USA

ISBN: (数字)9781728176871

ISBN: (纸本)9781728176888

Traditional aircraft control algorithms have a strong dependence on system models, and are difficult to cope with the increasingly complex battlefield environment for intelligent aircrafts. In this paper, a model-free reinforcement learning is proposed to solve an attitude stabilization problem of an aircraft based online intelligent control strategy. The attitude control problem is firstly formulated as an optimal control problem, and then an adaptive dynamic programming (ADP) technology is applied to compute the corresponding nonlinear Hamilton-Jacobi-Bellman (HJB) equation. Then, an actor-critic neural network structure is established to learn the optimal controller online not requiring the information of the aircraft dynamics. The proposed intelligent control strategy enables the aircraft to adjust its attitude according to the actual mission targets and environments under the proposed online control strategy, so that autonomous learning and intelligent operation can be realized. Finally, simulation examples are presented to validate the proposed model-free based control strategy.

关键词： Atmospheric modeling Aircraft Adaptation models Mathematical model Aerodynamics Attitude control Vehicle dynamics

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A Novel Relocating Recognition Algorithm in Overlapping Region for Multi-UAVs Cluster

A Novel Relocating Recognition Algorithm in Overlapping Regi...

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2022 IEEE International Conference on Unmanned systems, ICUS 2022

作者： Li, Chen Qi, Xuelei Zhao, Juntao Liao, Xuanhong Lin, Zitian Ma, Hongjun Liang, Xinkai College of Information Science and Engineering Northeastern University Shenyang China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Hong Kong Hong Kong High School Attached to Northeast Normal University International Curriculum Center Changchun China School of Automation Science and Engineering South China University of Technology Guangzhou China Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9781665484565

ISBN: (纸本)9781665484565

How improve the mapping efficiency and location accuracy of the multi-UAV cluster based on the distributed SLAM technology is a significant problem in overlapping regions. Therefore, this paper mainly proposes a novel relocation recognition algorithm for the multi-UAV cluster. First, the autonomous localization algorithm based on visual-inertial fusion is proposed. Then, the algorithm for vocabulary updating and relocating is designed. Finally, practical testing is implemented to verify and improve the efficiency of exploration ability and the accuracy of the autonomous navigation and positioning in the complex overlapping regions. © 2022 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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An Improved Task Planning Method for Unmanned Swarms with Coupled Physical and Logical Constraints

An Improved Task Planning Method for Unmanned Swarms with Co...

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2024 IEEE International Conference on Unmanned systems, ICUS 2024

作者： Chen, Xiubin Zhang, Lei Xu, Fang Yao, Weiran School of Astronautics Harbin Institude of Technology Harbin China Wuhan 2nd Ship Design and Research Institute Wuhan China Marine Military Intelligence Innovation Institute CSSC Systems Engineering Research Institute Beijing China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing China

ISBN: (纸本)9798350384185

Traditional task allocation methods for unmanned swarm systems ignore the effects of actual paths, resulting in estimation accuracy *** paper formulates task planning problem by incorporating physical and logical constraints, and establishes an integrated framework of task allocation and path ***-based search method is used to address path planning with physical constraints.A genetic algorithm is employed to solve multi-traveling salesman allocation problem.A bounded suboptimal optimization, a data dictionary, and an island model are introduced to accelerate the convergence speed of the genetic *** experiments verify that compared to the decoupled task planning methods, the proposed method improves task execution efficiency and remains adaptability to various complex spatial maps. © 2024 IEEE.

关键词： Genetic algorithms

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A Provably Stable SBP-SAT FDTD Subgridding Method without Modifying Yee's Grids

A Provably Stable SBP-SAT FDTD Subgridding Method without Mo...

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Antennas and Propagation Society International Symposium

作者： Yuhui Wang Guijie Diao Hong Ni Shunchuan Yang Research Institute for Frontier Science Beihang University Beijing China Beijing Electro-mechanical Engineering Institute Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory China

A stable finite-difference time-domain (FDTD) sub-grid ding method using the summation-by-parts simultaneous approximation term (SBP-SAT) technique is proposed. To meet the SBP properties and keep Yee's grids unchanged, the projection operators are carefully designed to extrapolate fields on the boundaries. Then, the SATs are used to weakly enforce the boundary conditions between multiple mesh blocks with different mesh sizes. Therefore, its long-term stability is theoretically guaranteed. An iris filter is simulated to validate the effectiveness of the proposed method. Results show that the proposed SBP-SAT FDTD subgridding method is stable, accurate and efficient.

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Method for Evaluating the Performance of Aircraft Collaborative Decision-Making Based on Dynamic Bayesian Network

Method for Evaluating the Performance of Aircraft Collaborat...

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Electronics and Devices, Computational science (ICEDCS), International Conference on

作者： Wenbo Zhang Boxiao Yu Jiahui Tong Jing Li National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing Electro-Mechanical Engineering Institute Beijing China School of Computer Science and Technology Beijing Institute of Technology Beijing China

ISBN: (数字)9798331527624

ISBN: (纸本)9798331527631

This research addresses the challenge of assessing equipment decision-making effectiveness in environments characterized by uncertainty and multiple influencing factors. We propose a novel approach involving the creation and optimization of a dynamic Bayesian network-based model tailored for equipment decision-making processes. The model facilitates a systematic evaluation of decision-making effectiveness by incorporating various factors, including equipment performance, environmental conditions, and enemy defensive capabilities. A comprehensive assessment system has been developed to simulate the penetration capabilities of different equipment through enemy defenses. Moreover, this study identifies potential errors in the effectiveness evaluation model by analyzing its performance in typical scenarios, pinpointing areas for enhancement.

关键词： Accuracy Uncertainty systematics Scientific computing Atmospheric modeling Computational modeling Decision making Data models Bayes methods Optimization

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