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41st Annual Conference of the IEEE Industrial Electronics Society, IECON 2015

作者： Roncero-Sanchez, Pedro Garcia, Xavier Del Toro Torres, Alfonso Parreno School of Industrial Engineering University of Castilla-La Mancha Ciudad Real Spain Robotics and Automation Centre Albacete Science and Technology Park Albacete Spain

ISBN: (纸本)9781479917624

Active power filters are key elements in both the removal of harmonic components caused by different loads and the maintenance of the power quality. Algorithms which extract the various harmonics from the waveform are therefore needed to generate the references for the active power filters. These algorithms normally extract the sum of all the undesired harmonics. Nevertheless, if it is necessary to compensate certain harmonics or if the individual information of each harmonic component is required, these algorithms are not valid. This work proposes the simultaneous estimation of the amplitudes of various harmonics by taking frequency deviations into consideration. The proposed algorithm uses robust discrete notch filters and approximately estimates the amplitudes of the harmonics in one cycle of the fundamental period. © 2015 IEEE.

关键词： Harmonic analysis

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Identifying the best machine learning algorithms for brain tumor segmentation, progression assessment, and overall survival prediction in the BRATS challenge

arXiv

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arXiv 2018年

作者： Bakas, Spyridon Reyes, Mauricio Jakab, Andras Bauer, Stefan Rempfler, Markus Crimi, Alessandro Shinohara, Russell Takeshi Berger, Christoph Ha, Sung Min Rozycki, Martin Prastawa, Marcel Alberts, Esther Lipkova, Jana Freymann, John Kirby, Justin Bilello, Michel Fathallah-Shaykh, Hassan M. Wiest, Roland Kirschke, Jan Wiestler, Benedikt Colen, Rivka Kotrotsou, Aikaterini Lamontagne, Pamela Marcus, Daniel Milchenko, Mikhail Nazeri, Arash Weber, Marc-Andr Mahajan, Abhishek Baid, Ujjwal Gerstner, Elizabeth Kwon, Dongjin Acharya, Gagan Agarwal, Manu Alam, Mahbubul Albiol, Alberto Albiol, Antonio Albiol, Francisco J. Alex, Varghese Allinson, Nigel Amorim, Pedro H.A. Amrutkar, Abhijit Anand, Ganesh Andermatt, Simon Arbel, Tal Arbelaez, Pablo Avery, Aaron Azmat, Muneeza Pranjal, B. Bai, Wenjia Banerjee, Subhashis Barth, Bill Batchelder, Thomas Batmanghelich, Kayhan Battistella, Enzo Beers, Andrew Belyaev, Mikhail Bendszus, Martin Benson, Eze Bernal, Jose Bharath, Halandur Nagaraja Biros, George Bisdas, Sotirios Brown, James Cabezas, Mariano Cao, Shilei Cardoso, Jorge M. Carver, Eric N. Casamitjana, Adri Castillo, Laura Silvana Cat, Marcel Cattin, Philippe Cérigues, Albert Chagas, Vinicius S. Chandra, Siddhartha Chang, Yi-Ju Chang, Shiyu Chang, Ken Chazalon, Joseph Chen, Shengcong Chen, Wei Chen, Jefferson W. Chen, Zhaolin Cheng, Kun Choudhury, Ahana Roy Chylla, Roger Clrigues, Albert Colleman, Steven Colmeiro, Ramiro German Rodriguez Combalia, Marc Costa, Anthony Cui, Xiaomeng Dai, Zhenzhen Dai, Lutao Daza, Laura Alexandra Deutsch, Eric Ding, Changxing Dong, Chao Dong, Shidu Dudzik, Wojciech Eaton-Rosen, Zach Egan, Gary Escudero, Guilherme Estienne, Tho Everson, Richard Fabrizio, Jonathan Fan, Yong Fang, Longwei Feng, Xue Ferrante, Enzo Fidon, Lucas Fischer, Martin French, Andrew P. Fridman, Naomi Fu, Huan Fuentes, David Gao, Yaozong Gates, Evan Gering, David Gholami, Amir Gierke, Willi Glocker, Ben Gong, Mingming Gonzlez-Vill, Sandra Grosges, T. Guan, Yuanfang Guo, Sheng Gupta, Sudeep Han, Woo-Sup Han, Il Song Harmuth, Ko Center for Biomedical Image Computing and Analytics University of Pennsylvania PhiladelphiaPA United States Department of Radiology Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Department of Pathology and Laboratory Medicine Perelman School of Medicine University of Pennsylvania PhiladelphiaPA United States Institute for Surgical Technology and Biomechanics University of Bern Bern Switzerland Center for MR-Research University Children's Hospital Zurich Zurich Switzerland Support Centre for Advanced Neuroimaging Inselspital Institute for Diagnostic and Interventional Neuroradiology Bern University Hospital Bern Switzerland University Hospital of Zurich Zurich Switzerland Center for Clinical Epidemiology and Biostatistics University of Pennsylvania Philadelphia United States Image-Based Biomedical Modeling Group Technical University of Munich Munich Germany Icahn School of Medicine Mount Sinai Health System New YorkNY United States Leidos Biomedical Research Inc. Frederick National Laboratory for Cancer Research FrederickMD21701 United States Cancer Imaging Program National Cancer Institute National Institutes of Health BethesdaMD20814 United States Department of Neurology University of Alabama at Birmingham BirminghamAL United States Department of Diagnostic Radiology University of Texas MD Anderson Cancer Center HoustonTX United States Department of Psychology Washington University St. LouisMO United States Neuroimaging Informatics and Analysis Center Washington University St. LouisMO United States Department of Radiology Washington University St. LouisMO United States Institute of Diagnostic and Interventional Radiology Pediatric Radiology and Neuroradiology University Medical Center Rostock Ernst-Heydemann-Str. 6 Rostock18057 Germany Tata Memorial Centre Homi Bhabha National Institute Mumbai India Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India NVIDIA Santa Clara

Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritumoral edematous/invaded tissue, necrotic core, active and non-enhancing core. This intrinsic heterogeneity is also portrayed in their radio-phenotype, as their sub-regions are depicted by varying intensity profiles disseminated across multi-parametric magnetic resonance imaging (mpMRI) scans, reflecting varying biological properties. Their heterogeneous shape, extent, and location are some of the factors that make these tumors difficult to resect, and in some cases inoperable. The amount of resected tumor is a factor also considered in longitudinal scans, when evaluating the apparent tumor for potential diagnosis of progression. Furthermore, there is mounting evidence that accurate segmentation of the various tumor sub-regions can offer the basis for quantitative image analysis towards prediction of patient overall survival. This study assesses the state-of-the-art machine learning (ML) methods used for brain tumor image analysis in mpMRI scans, during the last seven instances of the International Brain Tumor Segmentation (BraTS) challenge, i.e., 2012-2018. Specifically, we focus on i) evaluating segmentations of the various glioma sub-regions in pre-operative mpMRI scans, ii) assessing potential tumor progression by virtue of longitudinal growth of tumor sub-regions, beyond use of the RECIST/RANO criteria, and iii) predicting the overall survival from pre-operative mpMRI scans of patients that underwent gross total resection. Finally, we investigate the challenge of identifying the best ML algorithms for each of these tasks, considering that apart from being diverse on each instance of the challenge, the multi-institutional mpMRI BraTS dataset has also been a continuously evolving/growing dataset. Copyright © 2018, The Authors. All rights reserved.

关键词： Tumors

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Study of adhesion force between cellulose micro-sphere and cellulose membrane

Study of adhesion force between cellulose micro-sphere and c...

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International Conference on Manipulation, Manufacturing and Measurement on the Nanoscale (3M-NANO)

作者： Yuli Lai Pasi Kallio Hao Zhang Hui Xie Yasuhito Sugano Johan Bobacka Department of Automation Science and Engineering Tampere University of Technology Tampere Finland The State Key Laboratory of Robotics and Systems Harbin Institute of Technology Harbin China Department of Chemistry University of Helsinki Helsinki Finland Johan Gadolin Process Chemistry Centre Åbo Akademi University Turku Finland

ISBN: (纸本)9781509029464

Development of novel high added value cellulose products requires improved understanding of interaction forces, which includes also the adhesion force, between cellulose surfaces. However, the interaction forces between cellulose surfaces have not been adequately studied. In this paper, cellulose-cellulose adhesion force is studied by using a customized dual-probe atomic force microscope (AFM) with a cellulose colloidal probe. Two different types of cellulose membranes (CM) with cellulose concentration of 1.5% and 2% are used as test samples, and about ten thousand tests are repeated on each CM sample type. Adhesion force histograms are provided and they show a large difference between the two types of CM. The average adhesion force on CM 1.5% is approximately 10 times higher than that on CM 2%. On CM 1.5%, the adhesion forces concentrate on the range from 450nN to 650nN, whereas on CM 2% the force distribute from 50 to 75nN. The difference in the adhesion force on these two types of CM can be attributed to their difference in surface roughness and surface energy.

关键词： Probes Adhesives Force Surface topography Force measurement Rough surfaces Surface roughness

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Obstacle Avoidance for Kinematically Redundant Robot

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IFAC-PapersOnLine 2015年第28期48卷 490-495页

作者： WANG, Xinyu YANG, Chenguang CHEN, Junshen MA, Hongbin LIU, Feng School of Automation Beijing Institute of Technology Beijing China State Key Lab of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing China Centre for Robotics and Neural Systems Plymouth University Plymouth United Kingdom College of Automation Science and Engineering South China University of Technology Guangzhou China Beijing Jiaotong University Beijing China

Manipulator's obstacle avoidance is always a challenging topic in robotics. With the concern of the safety problems in human working environment, an improved obstacle avoidance method is proposed based on the general solution of the inverse kinematic problem of a redundant manipulator. A new obstacle detection method using Kinect R sensor is designed to give a robust obstacle information. By designing a parallel system of the manipulator, the proposed control method is not only to achieve the goal of moving away from the obstacle, but also able to guarantee the robot move back to its original pose. The stability of the closed-loop system is established using Lyapunov direct method to ensure the asymptotic stability of the system. The performance of the simulation results verifies the effectiveness of the proposed obstacle detection algorithm and the obstacle avoidance method. © 2015

关键词： Inverse problems Asymptotic stability Closed loop systems Collision avoidance Inverse kinematics Obstacle detectors Redundant manipulators System stability General solutions Inverse kinematic problems Kinematically Redundant Lyapunov direct method Obstacle detection Parallel system Redundant robot Working environment

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Development of a robotic teaching interface for human to human skill transfer

Development of a robotic teaching interface for human to hum...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Chenguang Yang Peidong Liang Arash Ajoudani Zhijun Li Antonio Bicchi Zienkiewicz Centre for Computational Engineering Swansea University UK State Key Lab of Robotics Systems Harbin Institute of Technology China Human-Robot Interfaces and Physical Interaction (HRI2) Laboratory of the Istituto Italiano di Tecnologia Genova Italy College of Automation Science and Engineering South China University of Technology Guangzhou China Interdepartmental Research Center "E. Piaggio" Faculty of Engineering University of Pisa Italy

ISBN: (纸本)9781509037636

The tutor-tutee hand-in-hand teaching may be the most effective approach for a tutee to acquire new motor skills. Repetitive nature of such procedures in a group setting usually results in a high labour cost and time inefficiency. Potential solution can be utilizing robotic platforms playing the role of tutors for demonstrating and transferring the required skills. This requires an appropriate guidance scheme to integrate the tutor's motor functionalities into the robot's control architecture. For instance, for hand-in-hand supervision of the writing task, the tutor's corrections can be applied when necessary, while a very compliant motion can be achieved if no errors are detected. Inspired by this behavior, we develop a teaching interface using a dual-arm robotic platform. In our setup, one arm is connected to the tutees arm providing guidance through a variable stiffness control approach, and the other to the tutor to capture the motion and to feedback the tutees performance in a haptic manner. The reference stiffness for the tutors arm stiffness is estimated in real-time and replicated by the tutees robotic arm. Comparative experiments have been carried out on a dual-arm Baxter robot. The results imply that the human tutor is able to intuitively transfer writing skills to the tutee and also show superior learning performance over over some conventional teaching by demonstration techniques.

关键词： Manipulators Robot sensing systems Impedance Training Muscles Manipulator sensing systems Manipulators impedance muscles Functional training Pedagogy Teaching LABOUR COSTS Human compliant motion Writing Skills Arm spiral arm Coaching Motor Skills

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Online Method for Simultaneous Extraction of Individual Harmonics in Three-Phase Systems

Online Method for Simultaneous Extraction of Individual Harm...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Pedro Roncero-Sanchez Xavier del Toro Garcia Alfonso Parreno Torres School of Industrial Engineering University of Castilla-La Mancha Robotics and Automation Centre Albacete Science and Technology Park

ISBN: (纸本)9781479917631

关键词： Harmonic analysis Frequency estimation Digital filters Power harmonic filters Power system harmonics Power quality

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Nominal Characteristics Trajectory Following Control as Practical Controller: A Review

Nominal Characteristics Trajectory Following Control as Prac...

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Annual Conference of the IEEE Industrial Electronics Society

作者： Shin-Horng Chong Kaiji Sato Centre of Excellence of Robotics & Industrial Automation Universiti Teknikal Malaysia Melaka Interdisciplinary Graduate School of Science & Engineering Tokyo Institute of Technology

ISBN: (纸本)9781479917631

Nominal Characteristic Trajectory Following (NCTF) control has been introduced and employed in positioning system since last two decades. It is well known with its practical and easy design procedure, which is independent of friction characteristics. Thus, designer does not need to consider the friction characteristic of a mechanism and it is a valuable controller approach in industry. Besides the straightforward design procedure, the NCTF controls are capable to achieve promising results in positioning and continuous motions and high robust performance as the end objective. The NCTF controller is comprehensive, comprising of a Nominal Characteristic Trajectory (NCT) and a PI compensator, which is free from exact modeling and parameter identification. There are three generations of the growth of NCTF controls, where it started as conventional NCTF control that emphasizes the motion of point-to-point. Then the NCTF control was improved in continuous motion where it has been named as Continuous Motion (CM) NCTF control. In order to enhance its motion accuracy and overshoot reduction characteristics, the acceleration element was added in the control structure, and namely Acceleration-Reference Continuous Motion (AR-CM) NCTF control. Although the control structure becomes slightly complicated, however, the design procedures of the three NCTF controls remain practical and easy. The usefulness of the NCTF controls have been clarified using the mechanisms with and without friction which in translation and rotary motions. The NCTF controls successfully demonstrated promising motion performances than the classical PID, PI-D and PDDO controllers in point-to-point, tracking and contouring motions.

关键词： NCTF control Ball screw system Rotary system Point-to-point motion Tracking motion point-to-point motion design process Control Architecture continual motion Standing Orders TRIBOLOGICAL PROPERTIES Controllers Nominal kinematic accuracy trajectory tracking control Positioning systems

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Learned ultra-wideband RADAR sensor model for augmented LIDAR-based traversability mapping in vegetated environments

Learned ultra-wideband RADAR sensor model for augmented LIDA...

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International Conference on Information Fusion

作者： Juhana Ahtiainen Thierry Peynot Jari Saarinen Steven Scheding Arto Visala Department of Electrical Engineering and Automation Aalto University Finland Science and Engineering Faculty Queensland University of Technology Australia GIM Ltd. Finland Australian Centre for Field Robotics University of Sydney Australia

ISBN: (纸本)9781479974047

In vegetated environments, reliable obstacle detection remains a challenge for state-of-the-art methods, which are usually based on geometrical representations of the environment built from LIDAR and/or visual data. In many cases, in practice field robots could safely traverse through vegetation, thereby avoiding costly detours. However, it is often mistakenly interpreted as an obstacle. Classifying vegetation is insufficient since there might be an obstacle hidden behind or within it. Some Ultra-wide band (UWB) radars can penetrate through vegetation to help distinguish actual obstacles from obstacle-free vegetation. However, these sensors provide noisy and low-accuracy data. Therefore, in this work we address the problem of reliable traversability estimation in vegetation by augmenting LIDAR-based traversability mapping with UWB radar data. A sensor model is learned from experimental data using a support vector machine to convert the radar data into occupancy probabilities. These are then fused with LIDAR-based traversability data. The resulting augmented traversability maps capture the fine resolution of LIDAR-based maps but clear safely traversable foliage from being interpreted as obstacle. We validate the approach experimentally using sensors mounted on two different mobile robots, navigating in two different environments.

关键词： Ultra wideband radar Robot sensing systems Laser radar Vegetation mapping Data models Feature extraction

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An automatic screw tightening shaft based on enhanced variable gain PID control

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International Journal of Simulation: Systems, science and Technology 2015年第5期16卷 14.1-14.9页

作者： Liu, Sibang Ge, Shuzhi Sam Qin, Gang Li, Min School of Automation Engineering University of Electronic Science and Technology of China ChengduSichuan611731 China Center for Robotics University of Electronic Science and Technology of China ChengduSichuan611731 China Department of Electrical and Computer Engineering National University of Singapore Singapore119077 Singapore Centre for Robotics University of Electronic Science and Technology of China ChengduSichuan611731 China School of Computer Science and Engineering University of Electronic Science and Technology of China ChengduSichuan611731 China

In this paper, a modular designed automatic screw tightening shaft system, which is based on enhanced variable gain PID control, is proposed. Designed for the autonomous screw tightening operation, the screw tightening shaft enjoys huge potential for industry application. The screw tightening shaft and the screw tightening process are both mathematically modeled as an uncertain feedback system because of the uncertain properties. And the control performance is verified by choosing proper controller parameters that the closed loop system is stable on the basis of the Routh stability criterion whereas the torque tracking error exponentially converges to a small residue. Furthermore, it can be seen from the simulation and experiment results on the screw tightening shaft system that the proposed autonomous system is valid and effective. © 2015, UK Simulation Society. All rights reserved.

关键词： Three term control systems

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Learning by observation for surgical subtasks: Multilateral cutting of 3D viscoelastic and 2D Orthotropic Tissue Phantoms

Learning by observation for surgical subtasks: Multilateral ...

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IEEE International Conference on robotics and automation (ICRA)

作者： Adithyavairavan Murali Siddarth Sen Ben Kehoe Animesh Garg Seth McFarland Sachin Patil W. Douglas Boyd Susan Lim Pieter Abbeel Ken Goldberg Department of Electrical Engineering and Computer Science (EECS) Center for Automation and Learning for Medical Robotics (Cal-MR) University of California Berkeley Berkeley CA USA Mechanical Engineering Ohio University Department of Electrical Engineering and Computer Science Athens OH US Division of Cardiothoracic Surgery University of California Davis Medical Center Sacramento CA USA Centre for Breast Screening and Surgery Centre for Robotic Surgery Singapore IEOR and EECS

Automating repetitive surgical subtasks such as suturing, cutting and debridement can reduce surgeon fatigue and procedure times and facilitate supervised tele-surgery. Programming is difficult because human tissue is deformable and highly specular. Using the da Vinci Research Kit (DVRK) robotic surgical assistant, we explore a “Learning By Observation” (LBO) approach where we identify, segment, and parameterize motion sequences and sensor conditions to build a finite state machine (FSM) for each subtask. The robot then executes the FSM repeatedly to tune parameters and if necessary update the FSM structure. We evaluate the approach on two surgical subtasks: debridement of 3D Viscoelastic Tissue Phantoms (3d-DVTP), in which small target fragments are removed from a 3D viscoelastic tissue phantom; and Pattern Cutting of 2D Orthotropic Tissue Phantoms (2d-PCOTP), a step in the standard Fundamentals of Laparoscopic Surgery training suite, in which a specified circular area must be cut from a sheet of orthotropic tissue phantom. We describe the approach and physical experiments with repeatability of 96% for 50 trials of the 3d-DVTP subtask and 70% for 20 trials of the 2d-PCOTP subtask. A video is available at: http://***/Robot-Surgery-Video-Oct-2014.

关键词： Phantoms Three-dimensional displays Surgery Motion segmentation Grippers Robot sensing systems

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