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Drogue detection for autonomous aerial refueling via hybrid pigeon-inspired optimized color opponent and saliency aggregation

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Chinese Journal of Aeronautics 2024年第5期37卷 27-38页

作者： Tongyan WU haibin duan Yanming FAN State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang UniversityBeijing 100083China Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng LaboratoryShenzhen 518000China AVIC Shenyang Aircraft Design and Research Institute Shenyang 110035China

Drogue detection is one of the challenging tasks in autonomous aerial refueling due to the requirement for accuracy and rapidity.Saliency detection based on image intrinsic cues can achieve fast detection,but with poor accuracy.Recent studies reveal that optimization-based methods provide accurate and quick solutions for saliency detection.This paper presents a hybrid pigeon-inspired optimization method,the optimized color opponent,that aims to adjust the weight of color opponent channels to detect the drogue region.It can optimize the weights in the selected aerial refueling scene offline,and the results are applied for drogue detection in the scene.A novel algorithm aggregated by the optimized color opponent and robust background detection is presented to provide better precision and robustness.Experimental results on benchmark datasets and aerial refueling images show that the proposed method successfully extracts the saliency region or drogue and exhibits superior performance against the other saliency detection methods with intrinsic cues.The algorithm designed in this paper is competent for the drogue detection task of autonomous aerial refueling.

关键词： Autonomous aerial refueling Drones Hybrid pigeon-inspired optimization Color opponent Saliency detection Saliency aggregation

UAV swarm air combat maneuver decision-making method based on multi-agent reinforcement learning and transferring

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Science China(Information Sciences) 2024年第8期67卷 49-66页

作者： Zhiqiang ZHENG Chen WEI haibin duan State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical Engineering Beihang University

During short-range air combat involving unmanned aircraft vehicle(UAV) swarms, UAVs must make accurate maneuver decisions based on information from both enemy and friendly UAVs. This dual requirement of competition and cooperation presents a significant challenge in the field of unmanned air combat. In this paper, a method based on multi-agent reinforcement learning(MARL) is proposed to address this issue. An actor network containing three subnetworks that can handle different types of situational information is designed. Hence, the results from simpler one-on-one scenarios are leveraged to enhance the complex swarm air combat training process. Separate state spaces for local and global information are designed for the actor and critic networks. A detailed reward function is proposed to encourage participation.To prevent lazy participants in air combat, a reward assignment operation is applied to distribute these dense rewards. Simulation testing and ablation experiments demonstrate that both the transfer operation and reward assignment operation can effectively deal with the swarm air combat scenario, and reflect the effectiveness of the proposed method.

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Distributed velocity-free formation tracking control for clustered UAVs under virtual leader-follower framework

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Science China(Technological Sciences) 2024年第5期67卷 1538-1552页

作者： ZHANG ZhaoYu duan haibin School of Automation Science and Electrical Engineering Beihang UniversityBeijing100083China

The collective formation control problem of a cluster of rotorcraft unmanned aerial vehicles(UAVs)is investigated in this article.The consensus tracking towards formation centroid with following UAVs forming a predefined configuration around the leader is considered as the objective.Unlike prior studies,the information of the central reference trajectory,which is deemed as a virtual leader in the leader-follower topology,is not directly accessible for partial nodes through the communication network.Therefore,a novel distributed formation tracking control scheme is promoted.Besides,a decentralized saturation observer is employed to estimate the reference acceleration signal of the virtual leader.In the absence of linear velocity measurement,two sliding manifolds are proposed by introducing the relative discrepancy terms of position and velocity.Then a smooth saturation operator in the form of a sigmoid function is applied to generate the command force input.Moreover,under the dilemma of constrained capabilities of the airborne sensors equipped on the rotorcrafts,the angular velocity is difficult to acquire.Two cascaded auxiliary attitude error systems are established on each rotorcraft system to synthesize the rotating torque with no need to require the angular velocity measurement.Due to the strong coupling and nonlinearity of the rotorcraft UAV system,the command angular velocity and the derivatives of command input are hard to obtain.Then a continuous nonlinear differentiator is proposed to work with the difficulties in deriving the explicit expression of system derivatives.Thereafter,a detailed stability analysis is conducted progressively on the angular control loop,reference trajectory observer loop,and the position control loop.A simulation scheme for a cluster of four rotorcraft UAVs tracking sinusoidal trajectory are presented and the formation control results are proven advantageous in comparison with the control protocol in previous literature.

关键词： distributed formation control unmanned rotorcraft clusters velocity-free tracking nonlinear differentiator

Extremum seeking control for UAV close formation flight via improved pigeon-inspired optimization

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Science China(Technological Sciences) 2024年第2期67卷 435-448页

作者： YUAN GuangSong duan haibin State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang University(BUAA)Beijing 100083China

This paper proposes a comprehensive design scheme for the extremum seeking control(ESC)of the unmanned aerial vehicle(UAV)close formation flight.The proposed design scheme combines a Newton-Raphson method with an extended Kalman filter(EKF)to dynamically estimate the optimal position of the following UAV relative to the leading UAV.To reflect the wake vortex effects reliably,the drag coefficient induced by the wake vortex is considered as a performance function.Then,the performance function is parameterized by the first-order and second-order terms of its Taylor series expansion.Given the excellent performance of nonlinear estimation,the EKF is used to estimate the gradient and the Hessian matrix of the parameterized performance function.The output feedback of the proposed scheme is determined by iterative calculation of the Newton-Raphson method.Compared with the traditional ESC and the classic ESC,the proposed design scheme avoids the slow continuous time integration of the gradient.This allows a faster convergence of relative position extremum.Furthermore,the proposed method can provide a smoother command during the seeking process as the second-order term of the performance function is taken into account.The convergence analysis of the proposed design scheme is accomplished by showing that the output feedback is a supermartingale sequence.To improve estimation performance of the EKF,a improved pigeon-inspired optimization(IPIO)is proposed to automatically tune the noise covariance matrix.Monte Carlo simulations for a three-UAV close formation show that the proposed design scheme is robust to the initial position of the following UAV.

关键词： unmanned aerial vehicle close formation extremum seeking control Newton-Raphson method improved pigeon-inspired optimization

From animal collective behaviors to swarm robotic cooperation

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National Science Review 2023年第5期10卷 82-99页

作者： haibin duan Mengzhen Huo Yanming Fan State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang University Virtual Reality Fundamental Research Laboratory Department of Mathematics and TheoriesPeng Cheng Laboratory AVIC Shenyang Aircraft Design and Research Institute

The collective behaviors of animals,from schooling fish to packing wolves and flocking birds,display plenty of fascinating phenomena that result from simple interaction rules among individuals.The emergent intelligent properties of the animal collective behaviors,such as self-organization,robustness,adaptability and expansibility,have inspired the design of autonomous unmanned swarm systems.This article reviews several typical natural collective behaviors,introduces the origin and connotation of swarm intelligence,and gives the application case of animal collective behaviors.On this basis,the article focuses on the forefront of progress and bionic achievements of aerial,ground and marine robotics swarms,illustrating the mapping relationship from biological cooperative mechanisms to cooperative unmanned cluster systems.Finally,considering the significance of the coexisting-cooperative-cognitive human-machine system,the key technologies to be solved are given as the reference directions for the subsequent exploration.

关键词： collective behaviors swarm intelligence cooperative robotics swarm human-machine system

A multi-strategy pigeon-inspired optimization approach to active disturbance rejection control parameters tuning for vertical take-off and landing fixed-wing UAV

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Chinese Journal of Aeronautics 2022年第1期35卷 19-30,I0001页

作者： Hangxuan HE haibin duan State Key Laboratory of Virtual Reality Technology and Systems Beihang UniversityBeijing 100191China Peng Cheng Laboratory Shenzhen 518000China

In this paper.Active Disturbance Rejection Control(ADRC)is utilized in the pitch control of a vertical take-off and landing fixed-wing Unmanned Aerial Vehicle(UAV)to address the problem of height fluctuation during the transition from hover to level flight.Considering the difficulty of parameter tuning of ADRC as well as the requirement of accuracy and rapidity of the controller,a Multi-Strategy Pigeon-Inspired Optimization(MSPIO)algorithm is employed.Particle Swarm Optimization(PSO),Genetic Algorithm(GA),the basic Pigeon-Inspired Optimization(PIO),and an improved PIO algorithm CMPIO are compared.In addition,the optimized ADRC control system is compared with the pure Proportional-Integral-Derivative(PID)control system and the non-optimized ADRC control system.The effectiveness of the designed control strategy for forward transition is verified and the faster convergence speed and better exploitation ability of the proposed MSPIO algorithm are confirmed by simulation results.

关键词： Active Disturbance Rejection Control(ADRC) Pigeon-inspired optimization algorithm Transition mode Unmanned Aerial Vehicle(UAV) Vertical take-off and landing

Create Machine Vision Inspired by Eagle Eye

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Research 2022年第4期2022卷 205-209页

作者： haibin duan Xiaobin Xu State Key Laboratory of Virtual Reality Technology and Systems School of Automation Science and Electrical EngineeringBeihang University(BUAA)Beijing 100083China Peng Cheng Laboratory Shenzhen 518055China

Eagle,a representative species in the raptor world,has the sharpest visual acuity among all animals.The reputation of the“clairvoyance”is employed to describe an eagle.The excellent visual skills of eagles depend on their unique eye structures and special visual principles.The powerful vision perception mechanisms of the eagle bring abundant inspiration for traditional visual applications.Biological eagle eye vision technology provides a creative way to solve visual perception issues of“Knowing What is Where by Seeing.”The theoretical research and practical works of eagle vision would contribute to the development of machine vision,or even artificial intelligence(AI)in the real world.Furthermore,eagle eye vision also provides feasible ideas for the popularization of new concepts in the virtual world in the future.

关键词： visual artificial Eagle

Autonomous Maneuver Decisions via Transfer Learning Pigeon-Inspired Optimization for UCAVs in Dogfight Engagements

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1639-1657页

作者： Wanying Ruan haibin duan Yimin Deng the School of Automation Science and Electrical Engineering Beihang University(BUAA)Beijing 100083China the State Key Laboratory of Virtual Reality Technology and Systems the School of Automation Science and Electrical EngineeringBeihang University(BUAA)Beijing 100083 Peng Cheng Laboratory Shenzhen 518000China

This paper proposes an autonomous maneuver decision method using transfer learning pigeon-inspired optimization(TLPIO)for unmanned combat aerial vehicles(UCAVs)in dogfight engagements.Firstly,a nonlinear F-16 aircraft model and automatic control system are constructed by a MATLAB/Simulink platform.Secondly,a 3-degrees-of-freedom(3-DOF)aircraft model is used as a maneuvering command generator,and the expanded elemental maneuver library is designed,so that the aircraft state reachable set can be obtained.Then,the game matrix is composed with the air combat situation evaluation function calculated according to the angle and range threats.Finally,a key point is that the objective function to be optimized is designed using the game mixed strategy,and the optimal mixed strategy is obtained by TLPIO.Significantly,the proposed TLPIO does not initialize the population randomly,but adopts the transfer learning method based on Kullback-Leibler(KL)divergence to initialize the population,which improves the search accuracy of the optimization algorithm.Besides,the convergence and time complexity of TLPIO are discussed.Comparison analysis with other classical optimization algorithms highlights the advantage of TLPIO.In the simulation of air combat,three initial scenarios are set,namely,opposite,offensive and defensive conditions.The effectiveness performance of the proposed autonomous maneuver decision method is verified by simulation results.

关键词： Autonomous maneuver decisions dogfight engagement game mixed strategy transfer learning pigeon-inspired optimization(TLPIO) unmanned combat aerial vehicle(UCAV)

Distributed game strategy for unmanned aerial vehicle formation with external disturbances and obstacles

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Frontiers of Information Technology & Electronic Engineering 2022年第7期23卷 1020-1031页

作者： Yang YUAN Yimin DENG Sida LUO haibin duan State Key Laboratory of Virtual Reality Technology and Systems School of Autonomous Science and Electrical EngineeringBeihang UniversityBeijing 100083China School of Mechanical Engineering&Automation Beihang UniversityBeijing 100191China Peng Cheng Laboratory Shenzhen 518000China

We investigate a distributed game strategy for unmanned aerial vehicle(UAV)formations with external disturbances and obstacles.The strategy is based on a distributed model predictive control(MPC)framework and Levy flight based pigeon inspired optimization(LFPIO).First,we propose a non-singular fast terminal sliding mode observer(NFTSMO)to estimate the influence of a disturbance,and prove that the observer converges in fixed time using a Lyapunov function.Second,we design an obstacle avoidance strategy based on topology reconstruction,by which the UAV can save energy and safely pass obstacles.Third,we establish a distributed MPC framework where each UAV exchanges messages only with its neighbors.Further,the cost function of each UAV is designed,by which the UAV formation problem is transformed into a game problem.Finally,we develop LFPIO and use it to solve the Nash equilibrium.Numerical simulations are conducted,and the efficiency of LFPIO based distributed MPC is verified through comparative simulations.

关键词： Distributed game strategy Unmanned aerial vehicle(UAV) Distributed model predictive control(MPC) Levy flight based pigeon inspired optimization(LFPIO) Non-singular fast terminal sliding mode observer(NFTSMO) Obstacle avoidance strategy