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IEEE Instrumentation and measurement Technology Conference

作者： C. Tarin Sauer H. Brugger E.P. Hofer B. Tibken Department of Measurement Control and Microtechnology Faculty of Electrical Engineering University of Ulm (EBS) Ulm Germany Department of Automation and Control F acult y of Electrical Engineering and Information Technology University of Wuppertal Wuppertal Germany

ISBN: (纸本)0780366468

A low cost navigation system is developed which fuses inertial sensor information provided by gyroscopes and odometry information. Both Kalman filters and a rule set based fusion strategy are used to correct the odometry errors in orientation for mobile robots. The fusion system even improves orientation estimation using a gyroscope with an extremely high drift rate. This navigation system is implemented on the autonomous mobile robot B21. The performance of this fusion method is tested on different surfaces and orientation errors do not increase as the robot travels along. Experimental results demonstrate that even in harsh environments with obstacles the performance of the designed navigation system reduces odometry tracking errors. The effects of nonsystematic odometry errors caused by unpredictable large bumps or objects encountered on the floor are reduced.

关键词： Error correction Sensor fusion Mobile robots Navigation control systems Sensor systems Electric variables measurement Gyroscopes Position measurement Automatic control

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Robust hover mode control of a tiltrotor using nonlinear control technique

Robust hover mode control of a tiltrotor using nonlinear con...

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AIAA Guidance, Navigation, and control Conference, 2016

作者： Alam, Mushfiqul Celikovsky, Sergej Walker, Daniel Department of Measurement Czech Technical University in Prague Czech Republic Department of Control Theory Institute of Information Theory and Automation Pod Vodarenskou Vezi 4 Praha 8CZ-182 08 Czech Republic School of Engineering Centre for Engineering Dynamics University of Liverpool The Quadrangle Brownlow HillL69 3GH United Kingdom

ISBN: (数字)9781624103896

ISBN: (纸本)9781624103896

Tiltrotor aircraft are complex, highly nonlinear systems which offers distinct operational advantages due to their unique Vertical Take-Off and Landing (VTOL) capabilities. Hovering a piloted tiltrotor in the helicopter flight condition is one of the most challenging tasks for pilots. Therefore, automatic control of the tiltrotor is always desired. Classical automatic linear control techniques fail to provide an adequate performance guarantee. In comparison, the application of nonlinear control techniques offers a potential alternative. Thus, in this paper modelling and hover control of a BELL XV-15 tiltrotor aircraft is presented. The MATLAB/Simulink based dynamic model of the BELL XV-15 tiltrotor aircraft is validated with respect to FLIGHTLAB model. In addition, a nonlinear hierarchical control strategy is adopted to provide automatic hover control of the tiltrotor aircraft. The results show a good hovering performance of the tiltrotor aircraft with small position tracking error. © 2016, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： automation

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An efficient method of small targets detection in low SNR

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Journal of Physics: Conference Series 2006年第1期48卷 427-430页

作者： Wang, Y.L. Dai, J.M. Sun, X.G. Wang, Q. Department of Automation Measurement and Control Engineering Harbin Institute of Technology Harbin 150001 PO Box 308 China

In this paper, an efficient method based on nonlinear adaptive filtering is proposed to detect the small IR target of low SNR under the complex background. The morphologic filter can be constructed firstly based on the IR radiation traits of low SNR small targets in the complex background and then a morphological method is used to eliminate the influence of the unbalance background to the image segmentation. Next an algorithm of adaptive threshold segmentation is adopted in order to select the small moving target and the noise points. Finally, on the basis of image sequences, the satisfactory targets detection is accomplished after eliminating wrong point targets. The method presented in this paper can effectively suppress the noise and the air background of the original image, enhance the ability of point target detection in single frame. © 2006 IOP Publishing Ltd.

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RGB-D Instance Segmentation-based Suction Point Detection for Grasping

RGB-D Instance Segmentation-based Suction Point Detection fo...

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2022 IEEE International Conference on Robotics and Biomimetics, ROBIO 2022

作者： Fu, Yeyu Sun, Ting Wang, Li Yu, Shijie Deng, Lei Chen, Baohua Li, Lin Xie, Yusen Deng, Shuixin Yin, Hanxi Beijing Information Science & Technology University Joint International Research Laboratory of Advanced Photonics and Elextronics Beijing China Beijing Institute of Control Engineering Space Optoelectronic Measurement and Perception Lab. Department of Perception Zhong-guancun Open Lab. Beijing China Tsinghua University Department of Automation Beijing China

ISBN: (纸本)9781665481090

Suction is a common way for robots to pick objects in industry, which has higher stability and reliability. However, it is necessary to evaluate the suction position on the object's surface when dealing with objects of different shapes. The previous method decouples it into a two-stage suction point detection and objects classification process, making the task more complex and time-consuming. On the other hand, there are significant challenges in acquiring training data. To address that, we propose an object instance segmentation-based suction grasping point detection method. Instance segmentation, as an object pixel-level perception method, can classify objects and find the orientation of objects in the plane, which is more efficient than simple classification. Specifically, our method generate a suction heatmap and object instance segmentation from RGB-D inputs and find the suction grasping position of each object after candidate points screening. To generate the training data, a heatmap mask based on 2D Gaussian-encoded is used to annotate the suction grasping ground truth. We evaluate each object's predicted suction grasping point results and conduct grasping experiments in real environments. The suction grasping success rate of 94% in dense scenes demonstrates the remarkable performance of the proposed method. © 2022 IEEE.

关键词： Object detection

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QMIX Algorithm for Coordinated Welding of Multiple Robots

QMIX Algorithm for Coordinated Welding of Multiple Robots

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作者： Liangchuang Liao Yang-Yang Chen School of Electronic Science & Engineering Southeast University Robot Department Jiangsu Automation Research Institute School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University

This paper considers the coordinated welding control based on deep multi-agent reinforcement *** discrete-time states and actions with local observation for the welding robots and the characteristics of the weld lines(e.g.,the starting points of the weld lines and the ending points of the weld lines) are defined,which is suitable to use the monotonic value function factorisation for deep multi-agent reinforcement learning(QMIX) algorithm.A novel reward composed of trajectory optimization,collision avoidance and the task done is designed,which is proved by the simulation in the grid-world environment.

关键词： Deep multi-agent reinforcement learning Welding robots QMIX

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Optimal Stochastic Production Scheduling for Uncertain Re-entrant Assembly Workshops

Optimal Stochastic Production Scheduling for Uncertain Re-en...

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2015 4th International Conference on Computer, Mechatronics, control and Electronic engineering (ICCMCEE 2015)

作者： Nanyun Jiang Hongsen Yan School of Automation and the MOE Key Laboratory of Measurement and Control of Complex Systems of Engineering Southeast University Department of Economics and Management Nanjing Technology University

ISBN: (纸本)9781510813465

An optimal stochastic problem of production scheduling for uncertain re-entrant assembly workshops(URAWs) was studied, in which the assembly process is repeated on the basis of quality inspection result and the number of repeats is uncertain. According to analysis of URAWs, a stochastic expected value model of production scheduling was built up. In order to solve the model conveniently, the model was then converted into a deterministic model. A genetic simulated annealing algorithm based on feasible region(FR-GSAA) was designed to solve this model. Finally the result of simulation examples indicates that the model and the algorithm are feasible and practical.

关键词： Uncertain Re-entrant Production Scheduling Genetic Simulated Annealing Algorithm

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Infrared image edge and texture analysis method based on visual habit

International Journal of Signal Processing, Image Processing...

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International Journal of Signal Processing, Image Processing and Pattern Recognition 2016年第10期9卷 179-186页

作者： Tian-He, Yu Xiao-Yang, Yu Jing-Min, Dai Harbin University of Science and Technology Harbin150080 China Department of Automation Measurement and control Engineering Harbin Institute of Technology Harbin150001 China

The general edge extraction algorithm is not ideal to process infrared images, which is low contrast and blurred edge. In this paper, we used the multi-fractal spectrum to edge of infrared image. We extracted the edge information of the image and calculate the measure and fractal spectrum with multiple singular values of each pixel. Analysis of the similarities and differences of multiple measure, the function in edge extraction, meanwhile, analyzed the fiction of fractal characteristics to edge image extraction. This method differs from the traditional gradient algorithm，It determines whether the edge or not just according to the local extreme points, but according to the pixels in the local and global relationships to determine whether the pixel is a real edge. It can neglect important edge pixel and texture pixel，which is more in line with the human visual mental. It provide a good reference for recognition of infrared image and further processing. © 2016 SERSC.

关键词： Edge detection

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A novel iris recognition method based on feature fusion

A novel iris recognition method based on feature fusion

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Peng-Fei Zhang De-Sheng Li Qi Wang Department of Automation Measurement and Control Harbin Institute of Technology China College of Mechanical Engineering & Applied Electronics Technology Beijing University of Technology China

ISBN: (纸本)0780384032

Although many approaches for iris recognition have been proposed in the last few years, few of them can perfect well in various image qualities. A novel method for iris recognition based on feature fusion is presented. Global and local iris features are extracted to improve the robustness of iris recognition for the various image quality. To represent the iris pattern efficiently, the global features are obtained from the 2D log Gabor wavelet filter and the local features are fused to complete the iris recognition. The weighting Euclidean distance and the Hamming distance are applied to match and classify. In addition, the thresholds are set up to reduce the computation time of match, and to increase robust iris recognition. Experimental results that confirm the benefits of using the proposed method are reported.

关键词： Iris recognition Feature extraction Image quality Robustness Gabor filters Hamming distance Image edge detection Lighting Encoding Independent component analysis

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Fusion of global and local feature based iris recognition

Fusion of global and local feature based iris recognition

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IEEE International Conference on Mechatronics and automation

作者： Pengfei Zhang Shaoshi Zhang Department of Automation Measurement and Control Harbin Institute of Technology Harbin Heilongjiang China Department of Astronautic Engineering and Mechanics Harbin Institute of Technology Harbin Heilongjiang China

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FlowDSnet: An End-to-End Scene Flow Based LiDAR De-Skewing Network

FlowDSnet: An End-to-End Scene Flow Based LiDAR De-Skewing N...

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2023 China automation Congress, CAC 2023

作者： Wu, Xinrui Zhu, Yixiang Wang, Siyi Yu, Zhenjun Wang, Guangming Wang, Hesheng Shanghai Jiao Tong University Department of Automation Shanghai China Shanghai Jiao Tong University Department of Electrical Engineering Shanghai China Shanghai Jiao Tong University Department of Measurement Control Technology Shanghai China SJTU-ParisTech Elite Institude of Technology Shanghai Jiao Tong University Shanghai China University of Cambridge Department of Engineering CambridgeCB2 1PZ United Kingdom

ISBN: (纸本)9798350303759

The motion distortion of LiDAR is the phenomenon caused by the movement of the LiDAR carrier. Such phenomenon makes the LiDAR point cloud information unreliable and seriously degrades the tasks that rely on LiDAR such as 3D object perception, localization, and mapping. In this work, a novel end-to-end network named FlowDSnet is proposed to compensate for the distortion of LiDAR point clouds in an end-to-end way. The proposed pipeline takes the original adjacent two frames of point clouds as input and recovers the undistorted coordinates of each point by predicting the scene flow in 3D space. Different from the traditional distortion removal algorithm, our method does not rely on the information of other sensors, such as the Inertial measurement unit (IMU), but applies a novel flow embedding algorithm combined with spatiotemporal interpolation to conduct distortion correction. And the input is two adjacent frames of raw LiDAR measurement. Besides, both qualitative and quantitative experiments on automative driving datasets are conducted to prove the effectiveness of the proposed pipeline. The experimental results show that this network can accomplish the LiDAR de-skewing task well, especially in a scene with many dynamic objects. © 2023 IEEE.

关键词： Pipelines

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