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IEEE/ASME (AIM) International Conference on advanced Intelligent Mechatronics

作者： Tan Zhang Dan Zhang Madan M. Gupta Wenjun Zhang Advanced Engineering Design Laboratory University of Saskatchewan Canada Robotics & Automation Laboratory University of Ontario Institute of Technology Canada Intelligent Systems Research Laboratory University of Saskatchewan Canada

Resilient robotic systems are a kind of robotic system that is able to recover their original function after partial damage of the system. This is achieved by making changes on the partially damaged robot. The general resilient robot, which makes sense by including active joints, passive joints, passive links, and passive adjustable links, was proposed in order to explore its resilience. The axiomatic design theory (ADT) is applied to develop the resilient robot. First, a general architecture of robots was proposed, which is characterized as under-actuated robot. Second, a docking system was developed, which is the key part of incorporating the proposed architecture in the design of the mechanical system of the resilient robot, and this thus enables the realization of the proposed architecture.

关键词： Joints Context Robot sensing systems Resilience Redundancy Connectors

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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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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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A HIERARCHICAL REINFORCEMENT LEARNING-BASED APPROACH TO MULTI-ROBOT COOPERATION FOR TARGET SEARCHING IN UNKNOWN ENVIRONMENTS

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CONTROL AND INTELLIGENT systems 2013年第4期41卷 1-1页

作者： Cai, Yifan Yang, Simon X. Xu, Xin Advanced Robotics and Intelligent Systems (ARIS) Laboratory School of Engineering University of Guelph Guelph ON N1G 2W1 Canada College of Mechatronics and Automation National University of Defense Technology Changsha Hunan Province 410073 China

Effective cooperation of multi-robots in unknown environments is essential in many robotic applications, such as environment exploration and target searching. In this paper, a MAXQ and Option combined hierarchical reinforcement learning approach, together with a multi-agent cooperation strategy, are proposed for the real-time cooperation of multi-robots in completely unknown environments. Unlike other algorithms that need an explicit environment model or selected parameters by trial and error, the proposed cooperation method obtains all the required parameters automatically through learning. By integrating segmental options with the MAXQ algorithm, a multi-agent cooperation strategy is designed. In new tasks, the designed cooperation method can control the multi-robot system to complete the task effectively. The simulation results demonstrate that the proposed scheme is able to effectively and efficiently guide a team of robots to cooperatively accomplish target searching tasks in completely unknown environments.

关键词： Hierarchical reinforcement learning multi-robot cooperation com-pletely unknown environment target searching

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Estimating the posture of pipeline inspection robot with a 2D Laser Rang Finder

Estimating the posture of pipeline inspection robot with a 2...

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2012 IEEE International Conference on Multisensor Fusion and Integration for Intelligent systems, MFI 2012

作者： Hu, Yuanyuan Song, Zhangjun Zhu, Jun ShenZhen Institutes of Advanced Technology China Academy of Science China Chinese University of Hong Kong Hong Kong Hong Kong Guangdong Provincial Key Laboratory of Robotics and Intelligent System China Information and Electrical Engineering China University of Mining and Technology China Mechanical Engineering and Automation South China University of Technology China

ISBN: (纸本)9781467325110

Pipeline network is one of the city's critical infrastructures, such as lots of gas pipes and water pipes exist in public utilities, factories and so on. Regular inspection is required to ensure the static integrity of the pipes and to insure against the problems associated with failure of the pipes. We have developed a pipeline inspection robot equipped with a camera which can walk in the pipes and stream back live video to the base station. In this paper we propose a new method for estimating the posture of the robot in round pipes with a 2D Laser Rang Finder (LRF) and a dual tilt-sensor by using the geometrical characteristic of the round pipes constructed with the point cloud data. Transformation matrix from the robot coordinate system to the global system is deduced. The positions and sizes of pipe defects can be calculated easily relying on the range data and images. Experiments by the inspection robot in dry smooth HDPE pipes are carried out and the results show that the proposed method is useful and valid. © 2012 IEEE.

关键词： Inspection

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SPARTAN system: Towards a low-cost and high-performance vision architecture for space exploratory rovers

SPARTAN system: Towards a low-cost and high-performance visi...

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2011 IEEE International Conference on Computer Vision Workshops, ICCV Workshops 2011

作者： Kostavelis, Ioannis Boukas, Evangelos Nalpantidis, Lazaros Gasteratos, Antonios Rodrigalvarez, Marcos Aviles Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece Advanced Space Systems and Technologies GMV Innovating Solutions Tres Cantos Madrid Spain

ISBN: (纸本)9781467300629

The "SPAring robotics Technologies for Autonomous Navigation" (SPARTAN) activity of the European Space Agency (ESA) aims to develop an efficient, low-cost and accurate vision system for the future Martian exploratory rovers. The interest on vision systems for space robots has been steadily growing during the last years. The SPARTAN system considers an optimal implementation of computer vision algorithms for space rover navigation and is designated for application to a space exploratory robotic rover, such as the ExoMars. The goal of the present work is the development of an appropriate architecture for the vision system. Thus, the arrangement and characteristics of the rover's vision sensors will be defined and the required computer vision modules will be presented. The analysis will be performed taking into consideration the constraints defined by ESA about the SPARTAN system. © 2011 IEEE.

关键词： Rovers

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SPARTAN system: Towards a low-cost and high-performance vision architecture for space exploratory rovers

SPARTAN system: Towards a low-cost and high-performance visi...

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International Conference on Computer Vision Workshops (ICCV Workshops)

作者： Ioannis Kostavelis Evangelos Boukas Lazaros Nalpantidis Antonios Gasteratos Marcos Aviles Rodrigalvarez Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece Advanced Space Systems and Technologies GMV Innovating Solutions Madrid Spain

The “SPAring robotics Technologies for Autonomous Navigation” (SPARTAN) activity of the European Space Agency (ESA) aims to develop an efficient, low-cost and accurate vision system for the future Martian exploratory rovers. The interest on vision systems for space robots has been steadily growing during the last years. The SPARTAN system considers an optimal implementation of computer vision algorithms for space rover navigation and is designated for application to a space exploratory robotic rover, such as the ExoMars. The goal of the present work is the development of an appropriate architecture for the vision system. Thus, the arrangement and characteristics of the rover's vision sensors will be defined and the required computer vision modules will be presented. The analysis will be performed taking into consideration the constraints defined by ESA about the SPARTAN system.

关键词： Cameras Three dimensional displays Robot vision systems Accuracy Mars

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Preliminary investigations on laminin coatings for flexible polyimide/platinum thin films for PNS applications

Preliminary investigations on laminin coatings for flexible ...

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Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)

作者： S. Bossi A. Benvenuto P. Wieringa G. Di Pino E. Guglielmelli T. Boretius T. Stieglitz X. Navarro S. Micera Systems Laboratory Scuola Superiore Sant Anna Advanced Robotics Technology Pontedera Italy Laboratory of Biomedical Robotics and Biomicrosystems Università Campus Bio-Medico di Roma Rome Italy Department of Microsystems Engineering IMTEK University of Freiburg Freiburg im Breisgau Germany Universitat Authnòma de Barcelona Barcelona Spain Institute of Automation Swiss Federal Institute of Technology Zurich Switzerland

The aim of this work was to investigate the possibility to obtain stable bioactive coatings for polyimide/platinum neural interfaces based on thin film technology for applications into the peripheral nervous system (PNS). Laminin (LI), a glycoprotein of the extracellular matrix, which guides and promotes differentiation and growth of neurons, was selected to deposit bioactive coatings. Dip-coating was performed on dummy structures at different LI concentrations. Indirect methods allowed to identify and characterize laminin on coated samples. Mechanical stability was also confirmed by indirect evaluations. Pilot experiments with differentiated PC12 cells, by the addition of nerve growth factor (NGF), showed improved neurite outgrowth on the coated probes compared to bare polyimide samples.

关键词： Polyimides Surface treatment Coatings Platinum Electrodes Microscopy

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F&A compensating variable bang-bang control algorithm for pneumatic driving glass-wall cleaning robot

F&A compensating variable bang-bang control algorithm for pn...

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2007 IEEE/RSJ International Conference on Intelligent Robots and systems

作者： W. Wang H. X. Zhang W. P. Yu G. H. Zong J. W. Zhang Robotics Institute School of Mechanical Engineering and Automation Beijing Aeronautics and Astronautics University Beijing China Institute of Technical Aspects of Multimodal Systems Department of Computer Science University of Hamburg Hamburg Germany Cognitive Technology Laboratory Shenzhen Institute of Advanced Technology Shenzhen China

To overcome the overshoot and oscillation in the normal Bang-Bang controller applied in the pneumatic driving glass-wall cleaning robot, this paper presents a F&A compensating variable Bang-Bang control algorithm for the pneumatic position servo. Besides a new cylinder driving plan is designed, the control algorithm is also improved by adding a fiction force compensating item in the chamber force evaluation equation. To adjust the controlling parameters dynamically, certain increasing functions, such as step function, linear function and arc-tangent function, are used to define the piston's expectative acceleration along with the reduction of the piston's position error. To testify the feasibility of the control algorithms with the above three expectative acceleration setting functions respectively, a pneumatic glass-wall cleaning robot "Sky Cleaner 4" is used as a testing platform to implement a series of on-load position servo experiments. And the different results of them are compared.

关键词： Bang-bang control Cleaning Robots Servomechanisms Testing Algorithm design and analysis Force control Equations Acceleration Error correction

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TRACKING CONTROL IN THE PRESENCE OF NONLINEAR DYNAMIC FRICTIONAL EFFECTS: ROBOT EXTENSION

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Asian Journal of Control 2008年第3期1卷

作者： M. Feemster D.M. Dawson A. Behal W. Dixon Matthew Feemster received the B.S degree in Electrical Engineering from Clemson University Clemson South Carolina in December 1994. Upon graduation he remained at Clemson University and received the M.S. degree in Electrical Engineering in 1997. During this time he also served as a research/teaching assistant. His research work focused on the design and implementation of various nonlinear control algorithms with emphasis on the induction motor and mechanical systems with friction present. He is currently working toward his Ph.D. degree in Electrical Engineering at Clemson University. Darren M. Dawson was born in 1962 in Macon Georgia. He received an Associate Degree in Mathematics from Macon Junior College in 1982 and a B.S. Degree in Electrical Engineering from the Georgia Institute of Technology in 1984. He then worked for Westinghouse as a control engineer from 1985 to 1987. In 1987 he returned to the Georgia Institute of Technology where he received the Ph.D. Degree in Electrical Engineering in March 1990. During this time he also served as a research/teaching assistant. In July 1990 he joined the Electrical and Computer Engineering Department and the Center for Advanced Manufacturing (CAM) at Clemson University where he currently holds the position of Professor. Under the CAM director's supervision he currently leads the Robotics and Manufacturing Automation Laboratory which is jointly operated by the Electrical and Mechanical Engineering departments. His main research interests are in the fields of nonlinear based robust adaptive and learning control with application to electro-mechanical systems including robot manipulators motor drives magnetic bearings flexible cables flexible beams and high-speed transport systems. Aman Behal was born in India in 1973. He received his Masters Degree in Electrical Engineering from Indian Institute of Technology Bombay in 1996. He is currently working towards a Ph.D in Controls and Robotics at Clemson University. His research focuses on the control of no

In this paper, we extend the observer/control strategies previously published in [25] to an n -link, serially connected, direct drive, rigid link, revolute robot operating in the presence of nonlinear friction effects modeled by the Lu-Gre model. In addition, we also present a new adaptive control technique for compensating for the nonlinear parameterizable Stribeck effects. Specifically, an adaptive observer/controller scheme is developed which contains a feedforward approximation of the Stribeck effects. This feedforward approximation is used in a composite controller/observer strategy which forces the average square integral of the position tracking error to an arbitrarily small value. Experimental results are included to illustrate the performance of the proposed controllers.

关键词： Friction compensation nonlinear control

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