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 poo...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.展开更多
The problem of cooperative circular formation with limited target information for multiple Unmanned Aerial Vehicle(UAV)system is addressed in this paper.A pigeon-inspired circular formation control method is proposed ...The problem of cooperative circular formation with limited target information for multiple Unmanned Aerial Vehicle(UAV)system is addressed in this paper.A pigeon-inspired circular formation control method is proposed to form the desired circular distribution in a plane based on the intelligent pigeon behavior during hovering.To reach the goal of prescribed radius and angular distribution,the controller is designed consisting of a circular movement part and a formation distribution part.Therein,the circular movement part is designed to make each UAV rotate around the speci-ed circle at the same angular speed only using the relative position between the UAV and the target.The formation distribution part could adjust the angular distance between each UAV and its neighbors with the jointly connected network to reduce communication cost.To smooth the speed variation,nonlinear PID-type method is delivered throughout the evolution of the system.The convergence analysis of the proposed control protocol is presented using Lyapunov theory and graph tools.The e®ectiveness of the proposed control strategies is demonstrated through numerical simulations.展开更多
Purpose–The purpose of this paper is to present weighted Euclidean distance for measuring whether the fitting of projective transformation matrix is more reliable in feature-based image stitching.Design/methodology/a...Purpose–The purpose of this paper is to present weighted Euclidean distance for measuring whether the fitting of projective transformation matrix is more reliable in feature-based image stitching.Design/methodology/approach–The hybrid model of weighted Euclidean distance criterion and intelligent chaotic genetic algorithm(CGA)is established to achieve a more accurate matrix in image stitching.Feature-based image stitching is used in this paper for it can handle non-affine situations.Scale invariant feature transform is applied to extract the key points,and the false points are excluded using random sampling consistency(RANSAC)algorithm.Findings–This work improved GA by combination with chaos’s ergodicity,so that it can be applied to search a better solution on the basis of the matrix solved by Levenberg-Marquardt.The addition of an external loop in RANSAC can help obtain more accurate matrix with large probability.Series of experimental results are presented to demonstrate the feasibility and effectiveness of the proposed approaches.Practical implications–The modified feature-based method proposed in this paper can be easily applied to practice and can obtain a better image stitching performance with a good robustness.Originality/value–A hybrid model of weighted Euclidean distance criterion and CGA is proposed for optimization of projective transformation matrix in image stitching.The authors introduce chaos theory into GA to modify its search strategy.展开更多
基金This work was partially supported by Science and Technology Innovation 2030-Key Project of“New Generation Artificial Intelligence”,China(No.2018AAA0102403)the National Natural Science Foundation of China(Nos.U1913602,T2121003,91948204,62103040,and U20B2071)the Open Fund/Postdoctoral Fund of the Laboratory of Cognition and Decision Intelligence for Complex Systems,Institute of Automation,Chinese Academy of Sciences(No.CASIA-KFKT-08).
文摘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.
基金This work was partially supported by Science and Technology Innovation 2030-Key Project of\New Generation Arti-cial Intelligence"under the Grant No.2018AAA0102405National Natural Science Foundation of China under the Grant Nos.91948204,U20B2071,U1913602,and U19B2033.
文摘The problem of cooperative circular formation with limited target information for multiple Unmanned Aerial Vehicle(UAV)system is addressed in this paper.A pigeon-inspired circular formation control method is proposed to form the desired circular distribution in a plane based on the intelligent pigeon behavior during hovering.To reach the goal of prescribed radius and angular distribution,the controller is designed consisting of a circular movement part and a formation distribution part.Therein,the circular movement part is designed to make each UAV rotate around the speci-ed circle at the same angular speed only using the relative position between the UAV and the target.The formation distribution part could adjust the angular distance between each UAV and its neighbors with the jointly connected network to reduce communication cost.To smooth the speed variation,nonlinear PID-type method is delivered throughout the evolution of the system.The convergence analysis of the proposed control protocol is presented using Lyapunov theory and graph tools.The e®ectiveness of the proposed control strategies is demonstrated through numerical simulations.
文摘Purpose–The purpose of this paper is to present weighted Euclidean distance for measuring whether the fitting of projective transformation matrix is more reliable in feature-based image stitching.Design/methodology/approach–The hybrid model of weighted Euclidean distance criterion and intelligent chaotic genetic algorithm(CGA)is established to achieve a more accurate matrix in image stitching.Feature-based image stitching is used in this paper for it can handle non-affine situations.Scale invariant feature transform is applied to extract the key points,and the false points are excluded using random sampling consistency(RANSAC)algorithm.Findings–This work improved GA by combination with chaos’s ergodicity,so that it can be applied to search a better solution on the basis of the matrix solved by Levenberg-Marquardt.The addition of an external loop in RANSAC can help obtain more accurate matrix with large probability.Series of experimental results are presented to demonstrate the feasibility and effectiveness of the proposed approaches.Practical implications–The modified feature-based method proposed in this paper can be easily applied to practice and can obtain a better image stitching performance with a good robustness.Originality/value–A hybrid model of weighted Euclidean distance criterion and CGA is proposed for optimization of projective transformation matrix in image stitching.The authors introduce chaos theory into GA to modify its search strategy.
