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Chinese control and decision Conference, CCDC

作者： Yubo Sun Xiyuan Shan Zhicheng Zong School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

ISBN: (纸本)9781665478977

In order to improve the dynamic performance of the underdriven crane system, an improved linear active disturbance rejection controller (LADRC) based on the new error was proposed. The improved LADRC takes the error value between the disturbance and its observed value multiplied by a coefficient as the basis for adjusting the linear extended state observer (LESO). The improved method has two advantages. Firstly, the new error can prevent the traditional LESO from choosing larger parameter adjustment disturbances, which will limit the performance of the observer. Secondly, the pole can be configured by adjusting the coefficient to obtain better dynamic characteristics. Finally, the effectiveness of the proposed method is verified by simulation and experiment. The proposed method can effectively restrain the swing of the payload and it is robust to system parameters perturbation as well.

关键词： Robust control Couplings Adaptation models Cranes Uncertainty Perturbation methods Bandwidth

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Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surface Vehicle in Marine Environment

Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surf...

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2020 IEEE International Conference on Information Technology, Big Data and Artificial Intelligence, ICIBA 2020

作者： Qi, Xianzhi Fu, Wenxing An, Pei Wu, Bingli Ma, Jie National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100071 China

ISBN: (纸本)9781728152240

Point cloud preprocessing is still a challenging task in the marine environment, for it is difficult to filter out non-obstacle points while avoiding damage to the obstacle completeness. In this paper, we propose a novel data preprocessing method on 3D LiDAR data for the unmanned surface vehicle in the marine environment. It consists of two tasks: outlier removal and wake filtering. As the spatial resolution of LiDAR changes with distance, we exploit distance normalization on statistical outlier filter for robust outlier removal. Considering the gradient difference between wave wake and obstacle surface near the water, we define and calculate the vertical state of point cloud on the range image to obtain the pre-filtering point set, and then use the RANSAC method to filter out the wake points. Experiments on real data has demonstrated the effectiveness of the proposed algorithm both in terms of feasibility and accuracy. © 2020 IEEE.

关键词： Wakes

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Low level saliency feature extraction method based on Hessian threshold

Low level saliency feature extraction method based on Hessia...

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Chinese automation Congress (CAC)

作者： Mingfang Du Junzheng Wang Jing Li Haiqing Cao Guangtao Cui Jianjun Fang Ji Lv Jiantao Pu Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China Automation School Beijing Union University Beijing China

The local invariant feature extraction algorithm SRUF (Speeded Up Robust Features) is introduced firstly. Then the new method of finding low level visual saliency feature based on SURF is deduced. The new method pay attention to Hessian matrix threshold and extract image features through changing the Hessian threshold. The number of saliency feature points change with the change of Hessian threshold. The visual saliency feature points will become sparser when Hessian threshold becomes larger. When some certain extreme thresholds which are defined as Hessian threshold Nodes are reached, the retained feature points are remarkable discriminative and stable feature points which make up the best sparse saliency features set. The feature extraction, matching and object recognition experiments of robot vision are finished to verify the new method. Experiment results show that the method is very effective.

关键词： Feature extraction Visualization Robots Robustness Heuristic algorithms Object recognition Educational institutions

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GAT-Net: A Network using Grid Attention and Transformer for Dynamic Facial Expression Recognition

GAT-Net: A Network using Grid Attention and Transformer for ...

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Chinese control and decision Conference, CCDC

作者： Wenxin Dai Yaping Dai Kaoru Hirota Shuai Shao School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing China

ISBN: (纸本)9781665478977

Dynamic facial expression recognition (DFER) in the wild has received widespread attention recently. There are complex factors such as face occlusion and pose variation in the wild. Facial expression recognition has a subtle competition between capturing local features of a human face and obtaining a global feature representation. This paper proposes an end-to-end DFER network GAT-Net based on the grid attention module and Transformer, which improves the robustness and accuracy of DFER in the wild. Specifically, GAT-Net is divided into two components: spatial feature extraction and temporal feature processing. The grid attention module of the spatial feature extraction component guides the network to pay attention to the local salient features of the face, which reduces the interference of field occlusion and non-frontal poses. The Transformer in the temporal feature processing component guides the network to learn the temporal relationship of high-level semantic features and the global representation of facial expression features. These two components balance the subtle competition between local features and global feature representations of facial expressions. The ablation experiment has proved the effectiveness of the grid attention module and Transformer. Experiments demonstrate that our GAT-Net outperforms state-of-the-art methods on DFEW and AFEW benchmarks with accuracies of 67.53%, and 50.14% respectively.

关键词： Face recognition Semantics Interference Benchmark testing Transformers Feature extraction Robustness

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Robot robust object recognition based on fast SURF feature matching

Robot robust object recognition based on fast SURF feature m...

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Chinese automation Congress (CAC)

作者： Mingfang Du Junzheng Wang Jing Li Haiqing Cao Guangtao Cui Jianjun Fang Ji Lv Xusheng Chen Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China Automation School Beijing Union University Beijing China

The local invariant features SURF (Speeded Up Robust Features) is introduced into the robot visual recognition field to solve scale changes, rotation, perspective changes, changes in illumination and other problems. A Speeded up SURF (SSURF) algorithm is proposed to meet the needs of robot visual identification. In SSURF algorithms, the main direction determination step of SURF algorithm is modified which make the search scope of the main direction becomes {-α, +α} (0 ≤ α ≤ 30°) from the original scope 360 According to compressed sensing ideas and interest points distribution histogram, the main scale search space is selected to improve the interest points searching step of SURF algorithm, so the interest points searching time-consuming is reduced. Matching the sample object and the scene using SSURF descriptor, and positioning the target position in the scene and giving ROI(region of interest). Experimental results in the autonomous mobile robot platform show that the proposed method significantly improves the speed of the robot to identify the target object, and proved robust to the scale changes, rotation, perspective changes, changes in illumination.

关键词： Feature extraction Robots Object recognition Robustness Vectors Image recognition Visualization

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Online Path Planning for UAV Using an Improved Differential Evolution Algorithm

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IFAC Proceedings Volumes 2011年第1期44卷 6349-6354页

作者： Xing Zhang Jie Chen Bin Xin Hao Fang School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Complex System Intelligent Control and Decision Ministry of Education Beijing 100081 China Tel: 86-10-68912464-22

Abstract This paper presents a 3D online path planning algorithm for unmanned aerial vehicle (UAV) flying in partially known hostile environment. In order to provide a smooth fight route for UAV, the algorithm adopts B-Spline curve to describe UAV's path whose control points are optimized by an improved differential evolution algorithm. The planner gradually produces a smooth path for UAV from starting location to its target. Regarding path planning performance, the proposed improved diferential evolution based planner is compared with its three competitors which are based on classical differential evolution, genetic algorithm and particle swarm optimization, respectively. Numerical simulation demonstrates that the proposed UAV path planner not only produces high-quality feasible flight routes for UAV, but also obviously outperforms its competitors.

关键词： UAV online path planning differential evolution B-Spline

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Design of a Novel Autonomous Docking system With a Supporting Robotic Fish

Design of a Novel Autonomous Docking System With a Supportin...

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2023 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2023

作者： Dong, Huijie Zhao, Chunyang Qiao, Tiezhu Wang, Jian Chen, Di Meng, Yan Yu, Junzhi Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education Taiyuan030024 China Chinese Academy of Sciences Laboratory of Cognitive and Decision Intelligence for Complex System Institute of Automation Beijing100190 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Guangdong Ocean University College of Electronics and Information Engineering Zhanjiang524088 China

ISBN: (纸本)9798350327182

Underwater supporting robots serving as a relay of energy supplements and communication for other underwater equipment are promising for ocean exploration, development, and protection. This paper proposes a novel autonomous docking system centered on a designed supporting robotic fish named 'CourierFish'. Specifically, CourierFish is capable of docking with a surface dock station for supplying itself and docking with a seafloor platform for supporting equipment in the platform. A visual navigation scheme integrating LED and ArUco markers is presented for accurate localization. The control approach for docking motion is also illustrated. Simulations and aquatic experiments are performed to verify the feasibility of the proposed docking system. The obtained results lay a solid foundation for the construction of various underwater equipment and robot networks. © 2023 IEEE.

关键词： Fish

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Interval Kalman Filter Based RFID Indoor Positioning

Interval Kalman Filter Based RFID Indoor Positioning

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第28届中国控制与决策会议

作者： Ning Li Hongbin Ma Chenguang Yang School of Automation Beijing Institute of Technology State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Zienkiewicz Centre for Computational Engineering Swansea University

ISBN: (纸本)9781467397155

Radio Frequency Identification(RFID) technology has shown its potential in the field of indoor positioning in recent years,and has been widely used in large establishments such as the airport lobby,supermarkets,libraries,underground parking and so ***,the complexity of the indoor environments make positioning a challenging problem in terms of accuracy,stability,reliability,and interference *** this paper,we develop an algorithm of passive RFID indoor positioning based on interval Kalman filter,according to the geometric constraints of responding tags,combined with the target motion *** interval Kalman filter is adopted to integrate target position of one preceding time point and reference tags position to estimate the current *** of this algorithm is to use passive tags to reduce hardware costs,and on the other hand the introduction of filtering algorithm improves the positioning accuracy.

关键词： RFID Indoor positioning Interval Kalman Filter Interval arithmetic

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Near Minimum-Time Feedback Attitude control with Multiple Saturation Constraints for Satellites

Near Minimum-Time Feedback Attitude Control with Multiple Sa...

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第三十四届中国控制会议

作者： Xing Xin Zhen Li Xiangdong Liu Zhen Chen School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781467374439

A near minimum time feedback control law is proposed for the agile satellite attitude control system. The real time controller is formed by specially designed cascaded subunits. Based on this, the rapid attitude maneuvering can be applied in tasks including the move to move case. The near optimal property of that is guaranteed by the rapid dynamic response with a modified bang-bang control logic while simultaneously ensuring non-saturation properties on 3-Axis. The near optimal method is utilized for an online attitude planning, and the generated attitude maneuver path in real time is tracked by a nonlinear back-stepping controller with its improved dynamic performance and by which the united closed loop control is *** simulations are conducted to verify the effectiveness of the proposed control strategy.

关键词： Attitude control,agile satellites,saturation control,back-stepping

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Modified EKF-based Nonlinear Filtering over Wireless Channels with Transmission Failure and Fading

Modified EKF-based Nonlinear Filtering over Wireless Channel...

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第35届中国控制会议

作者： Luyu Li Zhen Li Xiangdong Liu Yongzhi Sheng School of Automation Beijing Institute of Technology Key Laboratory for Intelligent Control & Decision on Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781509009107

This paper addresses the stochastic stability problem of a modified extended Kalman filter(MEKF), targeted at the state estimation of the nonlinear system through wireless channel, where both transmission failure and channel fading are practically under consideration. For a class of nonlinear systems whose observation's Jacobi Matrix is always invertible, the sufficient conditions of the error covariance matrices are accordingly established. Moreover, the conditions for the stochastic stability of the estimation error are also derived, which is tighter than the conditions of boundedness of the error ***, a numerical example is given to demonstrate the feasibility of the proposed method.

关键词： Extended Kalman filter stochastic stability transmission failure fading

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