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arXiv 2021年

作者： Wang, Guangming Ren, Shuaiqi Wang, Hesheng The Key Laboratory of System Control and Information Processing of Ministry of Education Department of Automation Institute of Medical Robotics Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai200240 China

Optical flow estimation is a fundamental problem of computer vision and has many applications in the fields of robot learning and autonomous driving. This paper reveals novel geometric laws of optical flow based on the insight and detailed definition of non-occlusion. Then, two novel loss functions are proposed for the unsupervised learning of optical flow based on the geometric laws of non-occlusion. Specifically, after the occlusion part of the images are masked, the flowing process of pixels is carefully considered and geometric constraints are conducted based on the geometric laws of optical flow. First, neighboring pixels in the first frame will not intersect during the pixel displacement to the second frame. Secondly, when the cluster containing adjacent four pixels in the first frame moves to the second frame, no other pixels will flow into the quadrilateral formed by them. According to the two geometrical constraints, the optical flow non-intersection loss and the optical flow non-blocking loss in the non-occlusion regions are proposed. Two loss functions punish the irregular and inexact optical flows in the non-occlusion regions. The experiments on datasets demonstrated that the proposed unsupervised losses of optical flow based on the geometric laws in non-occlusion regions make the estimated optical flow more refined in detail, and improve the performance of unsupervised learning of optical flow. In addition, the experiments training on synthetic data and evaluating on real data show that the generalization ability of optical flow network is improved by our proposed unsupervised approach. Copyright © 2021, The Authors. All rights reserved.

关键词： Computer vision

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Design and modeling of a compact rotational nonlinear spring

Design and modeling of a compact rotational nonlinear spring

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IEEE/RSJ International Conference on intelligent Robots and systems

作者： Hamed Jalaly Bidgoly Majid Nili Ahmadabadi Mohammad Reza Zakerzadeh Cognitive Robotics Laboratory The Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Iran Dynamic and Vibration Laboratory School of Mechanical Engineering College of Engineering University of Tehran Iran

ISBN: (纸本)9781509037636

In this paper, we propose a new method for implementing a rotational nonlinear spring with user defined profile, based on the combination of a linear spring with a nonlinear transmission mechanism. The proposed structure consists of a non-circular cam, a roller which moves along outer circumference of the cam, and a stretched translational linear spring which is connected between center of the cam and center of the roller. We obtain a set of differential equations to design shape of the cam for any given torque-angle profile. Also, it will be shown that profiles with both positive and negative values can be implemented by the proposed method. At last, the cam of some popular nonlinear springs are designed, including constant, cubic, hyperbolic tangent and sinusoidal springs.

关键词： Computer aided manufacturing Camelopardalis Hookean spring springs Device Spring TRANSFER MECHANISM Modeling nonlinearity Rotational SCROLL Differential equations Spring season

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A Multimodal Fault Diagnosis Model Utilizing GAF Transformation for controllable Pitch Propeller Hydraulic System

A Multimodal Fault Diagnosis Model Utilizing GAF Transformat...

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International Conference on control, Decision and Information Technologies (CoDIT)

作者： Huihuang Cai Wei Chen Huanglong Fu Hua Wang Jingcheng Wang Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education of China and Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Shanghai Marine Equipment Research Institute Shanghai China Department of Automation the Key Laboratory of System Control and Information Processing Ministry of Education of China and the Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Shanghai China Autonomous Systems and Intelligent Control International Joint Research Center Xi'an Technological University Xi'an China

ISBN: (数字)9798350373974

ISBN: (纸本)9798350373981

The hydraulic system of the controllable pitch propeller (CPP) serves as the power source for adjusting the blade pitch. Due to its structural complexity and harsh operating conditions, any malfunction of this system could significantly impair the vessel's navigation. Apart from the pitch command and the pitch feedback of CPP itself, the number and types of sensors added for fault diagnosis are not fixed. Therefore, this study establishes a multimodal fault diagnosis model based on Gramian angular field(GAF). By considering the deviation values of pitch feedback and pitch command as key variables, this model transforms them into a two-dimensional image using GAF, thereby obtaining more effective feature information. Image features are extracted using ResNet, while the temporal features of additional sensors are extracted using GRU. Finally, a multi-head attention mechanism is employed for feature fusion. This method achieves a classification accuracy of 100% in the classification of four types of hydraulic system faults simulated on the experimental platform.

关键词： Fault diagnosis Propellers Navigation Hydraulic systems Transforms Sensor phenomena and characterization Feature extraction Sensor systems Marine vehicles Load modeling

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MULTIPLE INSTANCE LEARNING VIA DISTANCE METRIC OPTIMIZATION

MULTIPLE INSTANCE LEARNING VIA DISTANCE METRIC OPTIMIZATION

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IEEE International Conference on Image processing

作者： Haifeng Zhao Jun Cheng Jun Jiang Dacheng Tao Sci. & Tech. on Information System Engineering Laboratory Nanjing 210007 China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Shenzhen Institutes of Advanced Technology CAS Shenzhen 518055 China Center for Quantum Computation and Intelligent Systems University of Technology Sydney 2007 Australia

ISBN: (纸本)9781479923427

Multiple Instance Learning (MIL) has been widely applied in practice, such as drug activity prediction, content-based image retrieval. In MIL, a sample, comprised of a set of instances, is called a bag. Labels are assigned to bags instead of instances. The uncertainty of labels on instances makes MIL different from conventional supervised single instance learning (SIL) tasks. Therefore, it is critical to learn an effective mapping to convert an MIL task to an SIL task. In this paper, we present OptMILES by learning the optimal transformation on the bag-to-instance similarity measure, exploring the optimal distance metric between instances, by an alternating minimization training procedure. We thoroughly evaluate the proposed method on both a synthetic dataset and real world datasets by comparing with representative MIL algorithms. The experimental results suggest the effectiveness of OptMILES.

关键词： Multiple instance learning distance metric learning MILES image classification alternating minimization MILES Image classification distance metric Squamous Intraepithelial Lesions Learning

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[email protected] : Analysis and results of evolving competitions for domestic and service robots

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Artificial Intelligence 2015年 229卷 258-281页

作者： Luca Iocchi Dirk Holz Javier Ruiz-del-Solar Komei Sugiura Tijn van der Zant Department of Computer Control and Management Engineering Sapienza University of Rome Italy Autonomous Intelligent Systems Group University of Bonn Germany Department of Electrical Engineering & Advanced Mining Technology Center Universidad de Chile Chile Information Services Platform Laboratory National Institute of Information and Communications Technology Japan Cognitive Robotics Laboratory University of Groningen The Netherlands

Scientific competitions are becoming more common in many research areas of artificial intelligence and robotics, since they provide a shared testbed for comparing different solutions and enable the exchange of research results. Moreover, they are interesting for general audiences and industries. Currently, many major research areas in artificial intelligence and robotics are organizing multiple-year competitions that are typically associated with scientific conferences. One important aspect of such competitions is that they are organized for many years. This introduces a temporal evolution that is interesting to analyze. However, the problem of evaluating a competition over many years remains unaddressed. We believe that this issue is critical to properly fuel changes over the years and measure the results of these decisions. Therefore, this article focuses on the analysis and the results of evolving competitions. In this article, we present the [email protected] competition, which is the largest worldwide competition for domestic service robots, and evaluate its progress over the past seven years. We show how the definition of a proper scoring system allows for desired functionalities to be related to tasks and how the resulting analysis fuels subsequent changes to achieve general and robust solutions implemented by the teams. Our results show not only the steadily increasing complexity of the tasks that [email protected] robots can solve but also the increased performance for all of the functionalities addressed in the competition. We believe that the methodology used in [email protected] for evaluating competition advances and for stimulating changes can be applied and extended to other robotic competitions as well as to multi-year research projects involving Artificial Intelligence and robotics.

关键词： Robotic competitions Artificial intelligence and robotics Benchmarking

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Extracting salient lines by Visual Attention for omnidirectional image classification

Extracting salient lines by Visual Attention for omnidirecti...

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IEEE Symposium on Computational Intelligence for Multimedia, Signal and Vision processing (CIMSIVP)

作者： AmirHossein Habibian Majid Nili-Ahmadabadi Babak Nadjar Araabi Robotics and AI Laboratory Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering Faculty of Engineering University of Tehran Tehran Iran School of Cognitive Sciences Institute for Research in Fundamental Sciences Tehran Iran

Representing an image as a set of its key and interesting lines facilitates the image understanding and classification. In this paper, we propose a method to extract the significant and interesting lines of the scene, which probably are useful in image classification. The proposed method is inspired from the Visual Attention, which is a perceptual mechanism in human and other primates that direct their perceptions to the limited regions of the scene. The attended regions are usually valuable in performing the task. Since the approach of using the lines to classify the images is particularly useful for omnidirectional images, we specialize our method to deal with these kinds of images. In the experiments, we demonstrate how our proposed methods improve the image classification performance with processing only small parts of the input images.

关键词： Feature extraction Visualization Image classification Gabor filters Image edge detection Histograms Computational modeling

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Model development of MIMO nets: a H-EPN based approach

Model development of MIMO nets: a H-EPN based approach

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IEEE Conference on Decision and control

作者： S. Ramaswamy K.P. Valavanis S. Barber The Laboratory for Intelligent Processes and Systems The Department of Electrical and Computer Engineering University of Texas Austin Austin TX USA The Robotics and Automation Laboratory The Center for Advanced Computer Studies and the Apparel-CIM Center University of Southwestern Louisiana Lafayette LA USA

The construction and analysis of multiple-input multiple-output (MIMO) subnets is discussed. It is shown that hierarchical time-extended Petri nets (H-EPNs) allow the development of structured MIMO subnets through the use of bottom-up Petri net synthesis techniques. The paper analyzes Petri net extensions that allow a truly hybrid approach to Petri net based systems modeling, analysis and development. The case study emphasizes the advantage of the activator arc extension in studying issues such as static priority scheduling, dynamic failure recognition, and rescheduling in manufacturing systems. The SPNP package, suitably modified to handle the H-EPN extensions, is used to analyze the properties of the derived H-EPN model.

关键词： MIMO Petri nets Failure analysis Job shop scheduling Dynamic scheduling Modeling Timing Manufacturing Packaging Solids

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Model Predictive control for Human Following Rehabilitation Robot

Model Predictive Control for Human Following Rehabilitation ...

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IEEE Workshop on advanced robotics and its Social Impacts, ARSO

作者： Shihao Yan Jing Tao Jian Huang Anshun Xue the Key Laboratory of the Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China Ministry of Civil Affairs of the People's Republic of China National Research Center for Rehabilitation Technical Aids Beijing China the Beijing Advanced Innovation Center of Intelligent Robots and Systems Beijing China

A new type of rehabilitation robot that can follow the user side-by-side is designed for aiding the elderly and disabled. The Human Following Rehabilitation Robot (HFRR) consists of a metal armrest, a set of sensors and a differential mobile base. By predicting the user's speed in the future through the user's current walking speed and the preset path, the problem of human following side-by-side is converted to a problem of keeping a certain lateral distance from the predicted trajectory. Linearizing the tracking error model, the nonholonomic mobile robot (NMR) can maintain a certain lateral distance from the trajectory by using Model Predictive control (MPC) and then follow the user side-by-side. The simulation and experimental results show the proposed controller can obtain good performance in this problem.

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A Low-Cost Vision-Based System for Displacement Analysis in Earthquake Research

A Low-Cost Vision-Based System for Displacement Analysis in ...

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RSI/ISM International Conference on robotics and Mechatronics

作者： Bijan Binaee Mahyar Khayatkhoei Hadi Moradi Amirhossein Nazemi Abdollah Hosseini Control and Intelligent Processing Center Advanced Robotics and Intelligent Systems Lab School of ECE University of Tehran Intelligent Systems Research Institute SKKU South Korea School of Civil Engineeringg College of Engineering University of Tehran

ISBN: (纸本)9781467372350

Measuring linear and angular displacement with high accuracy requires expensive equipment and may interfere with the measurements due to sensors weight and size. In this paper, we propose a low cost vision based approach for measuring linear & angular displacement that can make the earthquake research more *** keep detecting process as fast as possible and meet real-time demands, a typical marker with a peculiar color inside chooses and all instructions performed by Intel CVLib filters. So according to the tests, if the minimum requirement are met, the proposed method can detect marker up to 25 frames per second. Finally, a prototype software implemented to analysis functionality and accuracy of proposed algorithm. The results shown that this vision-based method can achieve accuracy of 0.1mm, with an off-the-shelf three pixel per millimeter, and it can be perfectly used instead of traditional instruments such as LVDT.

关键词： Rotoray-displacement tracking displacement tracking LVDT instrumentation shaking table seismology image processing

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Towards Collision Detection, Localization and Force Estimation for a Soft Cable-driven Robot Manipulator

Towards Collision Detection, Localization and Force Estimati...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Yuxin Wang Hesheng Wang Fan Xu Junzhi Yu Weidong Chen Yun-Hui Liu Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University Institute of Medical Robotics Key Laboratory of System Control and Information Processing of Ministry of Education Key Laboratory of Marine Intelligent Equipment and System of Ministry of Education Shanghai China College of Engineering Peking University Beijing China The Chinese University of Hong Kong Hong Kong

Soft robots have been applied widely to various constrained scenarios due to the advantages over traditional rigid manipulators such as softness, deformability and adaptability to constrained surroundings. To make full use of this merit, this paper proposes a method that integrates collision detection, localization and force estimation for a cable-driven soft manipulator without any prior geometrical knowledge of its surroundings. First of all, a collision detection algorithm is presented based upon Cosserat-rod statics by a threshold method through using the cable tension and the shape information, which are obtained by the load cells and the Vicon system, respectively. Secondly, a collision localization and force estimation method is proposed through optimizing the discrepancy between the actual and the theoretical shapes. Finally, experiments are carried out to validate these algorithms. The experimental results demonstrate that the site, the magnitude as well as the direction can be estimated.

关键词： Location awareness Shape Conferences Force Estimation Soft robotics Manipulators

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