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检索条件"机构=Science and Technology on Complex System Control"

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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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Influence of aircraft's maneuver flight performance parameters on within visual range air combat effectiveness 3

Influence of aircraft's maneuver flight performance paramete...

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3rd International Conference on Unmanned systems, ICUS 2020

作者： Zhen-Ning, Zhang Jia-Ning, W.E.I. Zhen-Biao, T.U. Fei-Fei, L.I. Beijing Electro-Mechanical Engineering Institute Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China

ISBN: (纸本)9781728180250

The fighter's war ability is closely related to its maneuver ability. The maneuver measurement index of the new generation fighter changed greatly compared to the traditional rules. This essay firstly introduced the modern fighter's maneuver performance quantized index. According to the built simulation system, take two typical third generation fighter models as the confront sides, built fuzzy control intelligent decision model based on the genetic algorithm, simulated the one-to-one air combat confront process. Under such circumstances, adjusted the maneuver flight performance parameters reasonable and got the confront simulation results, then analyzed and evaluated the influence of the parameterad justed within visual range air combat effectiveness, which provided reference significance to air combat flight's original design and maneuver flight performance parameter optimization. © 2020 IEEE.

关键词： Fuzzy control

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Aircraft Autonomous Positioning Based on a Coarse to Fine Multi-modal Image Registration Scheme

Aircraft Autonomous Positioning Based on a Coarse to Fine Mu...

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2021 IEEE International Conference on Power Electronics, Computer Applications, ICPECA 2021

作者： Sun, Fangde Fu, Wenxing Lu, Xiaohui Dong, Jing Han, Songlai Central South University School of Aeronautics and Astronautics Changsha China Science and Technology on Complex System Control Intelligent Agent Cooperation Laboratory Beijing China People's Liberation Army 91039th Unit Beijing China National University of Defense Technology Aerospace Science and Engineering Changsha China

ISBN: (纸本)9781728190037

In this paper, an autonomous positioning method based on coarse-to-fine multi-modal image matching is proposed for UAV navigation in GPS denied environment. Coarse image matching refers to roughly determining the approximate position of the real-time image in the reference image. Fine image matching refers to iterative matching around the position obtained by coarse image matching to achieve more accurate matching results. Besides, RANSAC is adopted to eliminate the outliers of image matching. After getting the result of image matching, we use PNP to estimate the position of the aircraft. The proposed position method has the advantages of high accuracy and reliability. The experimental results show that the average error of the position of the proposed method is 59%. © 2021 IEEE.

关键词： Image matching

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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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A SINS Error Correction Approach Based on Dual-Threshold ZV Detection and Cubature Kalman Filter

A SINS Error Correction Approach Based on Dual-Threshold ZV ...

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IEEE International Conference on systems, Man and Cybernetics

作者： Ruijie Xu Shichao Chen Wenqiao Sun Yisheng Lv Jialiang Luo Ying Tang The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences College of Information Science & Technology Beijing University of Chemical Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems The Center of National Railway Intelligent Transportation System Engineering and Technology Institute of Automation Chinese Academy of Sciences China Academy of Railway Sciences Corporation Limited Beijing China China Academy of Railway Sciences Corporation Limited Transportation and Economics Research Institute and the Center of National Railway Intelligent Transportation System Engineering and Technology Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing China The State Key Laboratory for Management and Control of Complex System State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences School of Information Engineering China University of Geosciences Beijing Beijing China Department of Electrical and Computer Engineering Rowan University Glassboro USA

Global Navigation Satellite systems (GNSS) can provide real-time positioning information for outdoor users, but cannot for indoor scenarios or heavily occluded outdoor scenarios. Strap-down Inertial Navigation system (SINS) are widely used to locate people in complex interior or heavily occluded outdoor scenarios due to its light weight and low power consumption. However, IMU of SINS are noisy, and the sampling data error is large, which is a divergence of the error with time. Therefore, it will generate a positioning accumulation error, which affects the final positioning accuracy. The problem of cumulative IMU errors is usually dealt with by Zero-Velocity Update (ZUPT). The zero-velocity detection part of basic ZUPT method usually uses a single threshold to determine the gait of pedestrian, which often has the problem of gait misjudgment and omission. To address these problems, this paper proposes a composite conditional detection method to solve the problem of misjudgment in the zero-velocity interval. In addition, we redesign the zero-velocity update algorithm and uses the Cubature Kalman filter (CKF) for pedestrian positioning error correction. The experimental results demonstrate that the proposed ZUPT method based on dual-threshold detection can better detect the interval between pedestrian motion and stationery than ones with single threshold. The zero-velocity update algorithm based on CKF has higher performance than conventional EKF and UKF methods, which constrains the cumulative error of SINS to about 0.2% of the whole walking distance.

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Safe Tracker: A Robust Aerial system for Safe Tracking in Cluttered Environments

Safe Tracker: A Robust Aerial System for Safe Tracking in Cl...

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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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Prediction of piRNA-mRNA interactions based on an interactive inference network

Prediction of piRNA-mRNA interactions based on an interactiv...

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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Yajun Liu Ru Li Aimin Li Rong Fei Xie Guo Fang-Xiang Wu Shaanxi Key Laboratory for Network Computing and Security Technology Xi'an University of Technology Xi'an China Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an University of Technology Xi'an China Department of Computer Science Department of Mechanical Engineering Division of Biomedical Engineering University of Saskatchewan Saskatoon Canada

As the largest class of small non-coding RNAs, piRNAs primarily present in the reproductive cells of mammals, which influence post-transcriptional processes of mRNAs in multiple ways. Effective methods for predicting piRNA and mRNA target relationships can help identify piRNA functions, investigate the possibility of piRNAs as biomarkers and therapeutic targets. In this study, we propose a computational approach for classifying the relationships of piRNA-mRNA pairs based on an interactive inference network (IIN). First, we gather piRNA-mRNA target data, collect sequence data by position alignment, and construct a benchmark dataset. Furthermore, a reliable negative set is constructed by positive-unlabeled learning. Finally, we view a piRNA and a mRNA sequence as a premise and hypothesis sentence, respectively, and IIN model is used to predict the relationship between them. The experiments demonstrate that our method effectively characterizes piRNA-mRNA interaction and could be beneficial for researchers to investigate piRNA functions.

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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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A belief rule-based fault diagnosis method for Multi-UAVs under missing attribute data

A belief rule-based fault diagnosis method for Multi-UAVs un...

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Cyber-Physical Social Intelligence (ICCSI), International Conference on

作者： ErKai Zhao MingRui Hao RuoHan Yang KeYuan Yue DeLin Yu School of Computer Science and Information Engineering Harbin Normal University Harbin China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing China School of Electronics and Information Northwestern Polytechnical University Xi’an China School of Mathematics and Statistics Northwestern Polytechnical University Xi’an China

To reasonably improve the missing attribute data and effectively integrate sample data and uncertain expert knowledge, this paper proposes a new fault diagnosis method based on a belief rule base (BRB). In the case of missing attribute data, the maximum likelihood estimation (MLE) method is used to complete the missing attribute data, and the fault diagnosis method of the multi-UAVs is constructed by using other complete attribute data as the input information of BRB. Finally, the effectiveness of the proposed method is verified by experimental simulation.

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