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Chinese control Conference (CCC)

作者： Yulin Hui Bailing Tian Xuewei Zhang Hanchen Lu Hongming Shen School of Electrical and Information Engineering Tianjin University Tianjin P. R. China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing P. R. China

This paper proposes Safe Tracker, an autonomous aerial tracking framework based on vision sensor that can deal with challenging tracking missions and guarantee safety and visibility. Firstly, a RGB-D sensor based segmentation method is employed to locate the target in real-time. Then target motion is predicted for a short time horizon, based on which a heuristic path searching method is applied to generate an occlusion-free path. Finally, particular formulations to balance visibility and safety are designed, and an effective non-linear trajectory optimization method enables to generate an optimal tracking trajectory. Autonomous aerial tracking experiments using a vision sensor are conducted to demonstrate the effectiveness of the proposed Safe Tracker in a challenging cluttered forest and a room full of sharp turns using Gazebo. Benchmark comparisons validate that our method tracks more safely and robustly than the state-of-art method.

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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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Research on the technology of cooperative dual-station position based on passive radar system 3

Research on the technology of cooperative dual-station posit...

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3rd International Conference on Unmanned systems, ICUS 2020

作者： Siting, Peng Qian, Zhao Yichao, Ma Jixiang, Jiang The Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728180250

When the aircraft adopt passive sensors to detect external conditions, the detection information we can directly get is the aspect Angle of target. However, the position, velocity, acceleration and other information of target need to be calculated through the relevant algorithm estimates. It need more passive sensor to work together in order to get more the target location information, because a single passive sensor can only give the arriving orientation and time of target signal. In view of the complex weather and sea wave situation at marine surrounding, a Cooperative dual-station positioning technology based on passive sensors is studied, and a Cooperative filtering method based on the theory of consensus is adopted to verify the algorithm performance and engineering significance through relevant simulation. © 2020 IEEE.

关键词： Kalman filters

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SeqEnhance: A Lightweight Image Processing PipeLine for Low-Light Image Enhancement

SeqEnhance: A Lightweight Image Processing PipeLine for Low-...

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Artificial Intelligence technology (ACAIT), Asian Conference on

作者： Runlin Zhou Peiliang Huang Dingwen Zhang Jun Ren AHU-IAI AI Joint Laboratory Anhui University Hefei China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei China School of Automation Northwestern Polytechnical University Xi’an China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (数字)9798350359145

ISBN: (纸本)9798350359152

Low-light image enhancement (LLIE) is an important task in computer vision, aiming to improve the visual perception or interpretability of images captured in poorly illuminated environments. Recently, deep learning based methods have been extensively explored to address this issue. While many of these methods have achieved significant advancements in various evaluation metrics for LLIE, only a few have made progress in improving inference speed for the resulting images. As a result, achieving both high-quality enhancements and efficient inference speed remains a challenge. To tackle this challenge, we propose SeqEnhance, a fast LLIE method based on a predefined parameterized image processing pipeline. Our approach combines the inference capabilities of deep neural networks for parameter estimation and the efficient processing capabilities of image processing pipelines to generate enhanced images in an end-to-end manner. The experimental results demonstrate that the proposed method achieves competitive performance on image quality evaluation metrics such as PSNR and SSIM with a fast inference speed.

关键词： Measurement Image quality Deep learning Computer vision Parameter estimation Pipelines Artificial neural networks

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Tightly-Coupled Lidar-Visual-Inertial Odometry and Mapping in Real Time

Tightly-Coupled Lidar-Visual-Inertial Odometry and Mapping i...

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Chinese control Conference (CCC)

作者： Wenyu Ma Bailing Tian Hanchen Lu Hongming Shen School of Electrical and Information Engineering Tianjin University Tianjin P. R. China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing Electro-Mechanical Engineering Institute Beijing P. R. China

We proposed a tightly-coupled Lidar-visual-inertial odometry and mapping method, which takes advantage of measurement of Lidar, visual and inertial sensors to achieve highly accurate, real-time 6DoF state estimation and map-building in GNSS-denied environments. The proposed odometry is a tightly-coupled optimization-based method, obtains robust and low drift odometry by fusing pre-integrated IMU measurements, visual features from the image, and geometric features from Lidar data. Further, we adapt an online method to mitigate degeneracy in optimization problems to improve robustness in environmentally degenerate cases. Simulation and real-world experiments show that the proposed method exhibits similar or better robustness and accuracy with the state-of-the-art SLAM methods.

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Multilevel filtering image denoising algorithm based on edge information fusion 16

Multilevel filtering image denoising algorithm based on edge...

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16th National Conference on Laser technology and Optoelectronics

作者： Zhang, Xin Sun, Jianfeng Jiang, Peng Zhou, Xin Qiu, Changrui Zhang, Yinbo Zhang, Hailong National Key Laboratory of Science and Technology on Tunable Laser Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Industrial Technology Innovation Research Institute Co. Ltd Beijing101312 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China

ISBN: (数字)9781510646643

ISBN: (纸本)9781510646636

Edges are critical important for the visual appearance of images. The traditional denoising algorithms are difficult to preserve the edges of the image while removing the noise of ICCD sensing image. At the same time, it is difficult to eliminate the problems of image darkness and low resolution caused by uneven illumination. This paper proposes a multilevel filtering image denoising algorithm based on edge information fusion. The target edges detection of the image after non-local means (NL-means) filtering is carried out based on the eight-direction Sobel operator. In order to filter the false edge points and residual noise, an adaptive threshold is determined according to the mean and variance of the eight neighborhood pixels of the detected pixel. Meanwhile, homomorphic filtering is used to enhance the image contrast and uniformity. By comparing the pixel values of the edge image and the homomorphic filtered image, the final denoised image is obtained by fusing the two images. The results indicate that, compared with the traditional algorithms, the edge preserving ability of the proposed algorithm is improved by more than 20%, and the denoising ability is improved by 63.5% for building target. For specific targets (vehicle), the results demonstrate that the proposed algorithm have the maximum edge preserving index and contrast, and the minimum non-uniformity. This algorithm lays a foundation for target segmentation and recognition. © 2021 SPIE.

关键词： Image fusion

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Depth imaging through realistic fog using Gm-APD Lidar 16

Depth imaging through realistic fog using Gm-APD Lidar

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16th National Conference on Laser technology and Optoelectronics

作者： Zhang, Yinbo Li, Sining Jiang, Peng Sun, Jianfeng Liu, Di Yang, Xianhui Zhang, Xin Zhang, Hailong National Key Laboratory of Science and Technology on Tunable Laser Institute of Opto-Electronic Harbin Institute of Technology Heilongjiang Harbin150001 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Industrial Technology Innovation Research Institute Co. Ltd Beijing101312 China

ISBN: (数字)9781510646643

ISBN: (纸本)9781510646636

When using Gm-APD Lidar for depth imaging through realistic fog, the echo signal of the target is submerged in the background noise due to the strong absorption and scattering characteristics of the fog particles, resulting in serious defect of the recovered depth image of the target. To solve this problem, this paper proposes a dual-parameter estimation algorithm based on continuous wavelet transform (CWT) and maximum likelihood estimation (MLE) to improve the accuracy of fog signal estimation. Then the target and the fog signal are separated by estimating the fog signal of each pixel. Finally, the depth image of the separated target is processed by cross pixel complement and median filtering algorithms to improve the integrity of the target image. The experimental results show that, compared with the traditional algorithm, the target recovery of the reconstructed image is improved by 0.337, and the relative average ranging error is reduced by 0.3897. This research improves the weather adaptability of Gm-APD Lidar. © 2021 SPIE.

关键词： Optical radar

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Adaptive terminal sliding mode control for flexible air-breathing hypersonic vehicle

Adaptive terminal sliding mode control for flexible air-brea...

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AIAA science and technology Forum and Exposition, AIAA SciTech Forum 2021

作者： Qin, Decong Chen, Haibing Lin, Wei Tang, Peng Ma, Tielin Xu, Cheng School of Transportation Science and Engineering Beihang University Beijing China Aircraft/Engine Integrated System Safety Beijing Key Laboratory Beijing China Beijing System Design Institute of the Electro-mechanic Engineering Beijing China Institute of Unmanned System Beihang University Beijing China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781624106095

Flexible air-breathing hypersonic vehicles show significant and complex aerodynamic, scramjet propulsion system, flight dynamic and elastic coupling characteristics, which usually are highly nonlinear. These result in huge uncertainties, parameter perturbation and internal disturbance, which can no longer be ignored, and therefore, extreme difficulties for flight control design. A unique parameter adaptive non-singular terminal sliding mode method is proposed for longitudinal control law design of a flexible coupling air-breathing hypersonic vehicle. This method uses adaptive reaching law gain instead of additional adaptive compensation term to handle the uncertainty to improve robustness. The stability of the close loop system is proved via a Lyapunov way. The longitudinal tracking control law for velocity and angle of attack is designed based on a rigid dynamic model of a flexible air-breathing hypersonic vehicle. A strong coupling model of the same vehicle, considering aerodynamic-scramjet engine-flight dynamic-elastic couplings, is established as the verification platform of control law designed. Simulation results obtained based on the coupling model demonstrate that the control law designed has good performance and acceptable robustness. © 2021, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Hypersonic vehicles

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Time series generator adversarial network with stochastic process for the degradation generation and prediction

Time series generator adversarial network with stochastic pr...

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Data Driven control and Learning systems (DDCLS)

作者： Anqi Shangguan Nan Feng Lingxia Mu Rong Fei Xinhong Hei Guo Xie Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China School of computer science and Engineering Xi'an University of Technology Xi'an China

Since the cumbersome collection process and high cost, the collected degradation of the product is basically small samples, which will affect the accuracy of reliability evaluation. It is necessary to expand the degradation to improve the accuracy of later reliability assessment. Therefore, a degradation generation and prediction method is proposed combining the time series generator adversarial network (TimeGAN) and stochastic process. Firstly, the input degradation is expanded by the sliding window to improve the later training accuracy; Then, the construction of the generator in TimeGAN is linked with the stochastic process to make the generation data more realistic. Finally, the results of degradation prediction by the Gated Recurrent Unit (GRU) can be obtained. Two datasets and different generation methods are adopted to evaluate the effectiveness of the proposed method. The results shows that the Kullback-Leibler(KL) divergence is the smallest, and the prediction error is the smallest compared with the other methods. So, the proposed method is proved that it is valid in the degradation generation and prediction, and can be used for the further reliability assessment of the product in the industrial system.

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Fast Vision Decoder: A Robust Automatic Target Recognition Model for Sar Images

SSRN

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SSRN 2022年

作者： Ayodeji, Abiodun Wang, Wenhai Su, Jianzhong Yuan, Jianquan Liu, Xinggao State Key Laboratory of Industrial Control Technology Control Department Zhejiang University Hangzhou310027 China Tianjin Jinhang Technical Physics Institute Tianjin300192 China Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing100074 China

The synthetic aperture radar (SAR) is the recent all-weather technology used to monitor areas with low to moderate penetration. However, the scarcity of SAR imagery, and the high-level noise in the images makes it difficult for real-time image interpretation. This work presents a novel fast vision decoder (FViD), a target recognition model with a frozen backbone and stack dilated autoencoder. The autoencoder architecture is introduced to learn the compressed latent representation. Moreover, a robust backbone selection method is introduced to select a task-specific optimal backbone. The proposed FViD is extensively evaluated using the Chinese TerraSAR-X ship images, and the US MSTAR datasets. Evaluation results show that the proposed method has significant improvement over the conventional models. The speed and accuracy of the proposed FViD are further compared with five state of the art models previously used for SAR target recognition tasks, and the comparison result shows that the FViD performs better. Moreover, an ablation study is performed to provide insights into the contribution of FViD architecture. The results of the ablation study as well as the performance improvement of FViD are discussed in this paper. © 2022, The Authors. All rights reserved.

关键词： Computer vision

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