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International Conference on Advanced robotics (ICAR)

作者： Barry Ridge Emre Ugur Aleš Ude Department of Automation Biocybernetics and Robotics Jožef Stefan Institute Ljubljana Slovenia Intelligent and Interactive Systems Laboratory University of Innsbruck Austria

Recent work in robotics, particularly in the domains of object manipulation and affordance learning, has seen the development of action-grounded features, that is, object features that are defined dynamically with respect to manipulation actions. Rather than using pose-invariant features, as is often the case with object recognition, such features are grounded with respect to the manipulation of the object, for instance, by using shape features that describe the surface of an object relative to the push contact point and direction. In this paper we provide an experimental comparison between action-grounded features and non-grounded features in an object affordance classification setting. Using an experimental platform that gathers 3-D data from the Kinect RGB-D sensor, as well as push action trajectories from an electromagnetic tracking system, we provide experimental results that demonstrate the effectiveness of this action-grounded approach across a range of state-of-the-art classifiers.

关键词： Three-dimensional displays Feature extraction Shape Trajectory Robot sensing systems Training

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Switching to Learn

Switching to Learn

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American Control Conference

作者： Shahin Shahrampour Mohammad Amin Rahimian Ali Jadbabaie Department of Electrical and Systems Engineering and General Robotics Automation Sensing and Perception (GRASP) Laboratory University of Pennsylvania Philadelphia PA 19104-6228 USA

ISBN: (纸本)9781479917730

A network of agents attempt to learn some unknown state of the world drawn by nature from a finite set. Agents observe private signals conditioned on the true state, and form beliefs about the unknown state accordingly. Each agent may face an identification problem in the sense that she cannot distinguish the truth in isolation. However, by communicating with each other, agents are able to benefit from side observations to learn the truth collectively. Unlike many distributed algorithms which rely on all-time communication protocols, we propose an efficient method by switching between Bayesian and non-Bayesian regimes. In this model, agents exchange information only when their private signals are not informative enough;thence, by switching between the two regimes, agents efficiently learn the truth using only a few rounds of communications. The proposed algorithm preserves learnability while incurring a lower communication cost. We also verify our theoretical findings by simulation examples.

关键词： Switches Bayes methods Convergence Robot sensing systems Symmetric matrices Protocols Silicon

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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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Dynamic modeling and control simulation of a modified delta manipulator

Dynamic modeling and control simulation of a modified delta ...

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2015 IEEE International Conference on Information and automation, ICIA 2015 - In conjunction with 2015 IEEE International Conference on automation and Logistics

作者： Hao, Jianlong Xie, Xiaoliang Bian, Guibin Feng, Zhenqiu Gao, Zhanjie Hou, Zengguang Yu, Hongnian Vladareanu, Luige State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Faculty of Science and Technology Bournemouth University Poole DorsetBH12 5BB United Kingdom Robotics and Mechatronics Department Institute of Solid Mechanics Romanian Academy 15 C-tin Mille Street Bucharest 1 Romania

ISBN: (纸本)9781467391047

The delta parallel mechanism has proven to be a very successful parallel robot design and a number of variants have been proposed in the literature. Taking advantage of its simple construction and the intrinsic features such as high stiffness and accuracy, delta robots play an important role both in the fields of industrial robots and academical fields. In this paper, dynamic modeling and control simulation of a cable-driven modified delta manipulator for haptic interface are discussed. For the parallel mechanism is highly coupled and nonlinear, the dynamic model is of great importance for model-based controller to achieve a satisfactory performance. Based on the principle of virtual work, the dynamic equations of this manipulator are established. The proportional-derivative (PD) computed torque control scheme is proposed for trajectory tracking. With the help of the virtual prototype builded in ADAMS software and used in MATLAB software, the co-simulation is accomplished and the results validate the performance of the controller proposed in this paper. © 2015 IEEE.

关键词： Manipulators

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Implementation and test of human-operated and human-like adaptive impedance controls on Baxter robot

Implementation and test of human-operated and human-like ada...

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15th Annual Conference on Advances in Autonomous robotics systems, TAROS 2014

作者： Liang, Peidong Yang, Chenguang Wang, Ning Li, Zhijun Li, Ruifeng Burdet, Etienne Centre for Robotics and Neural Systems School of Computing and Mathematics Plymouth University United Kingdom MOE Key Lab. of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology China State Key Laboratory of Robotics and System Harbin Institute of Technology China Department of Computer Science and Engineering Chinese University of Hong Kong Hong Kong Department of Bioengineering Imperial College of Science Technology and Medicine London United Kingdom

ISBN: (纸本)9783319104003

This paper presents an improved method to teleoperate impedance of a robot based on surface electromyography (EMG) and test it experimentally. Based on a linear mapping between EMG amplitude and stiffness, an incremental stiffness extraction method is developed, which uses instantaneous amplitude identified from EMG in a high frequency band, compensating for non-linear residual error in the linear mapping and preventing muscle fatigue from affecting the control. Experiments on one joint of the Baxter robot are carried out to test the approach in a disturbance attenuation task, and to compare it with automatic human-like impedance adaptation. The experimental results demonstrate that the new human operated impedance method is successful at attenuating disturbance, and results similarly to as automatic disturbance attenuation, thus demonstrating its efficiency. © 2014 Springer International Publishing.

关键词： Stiffness

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Moment-based Dirac Mixture Approximation of Circular Densities

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IFAC Proceedings Volumes 2014年第3期47卷 5040-5048页

作者： Uwe D. Hanebeck Anders Lindquist Intelligent Sensor-Actuator-Systems Laboratory (ISAS) Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology (KIT) Germany Department of Automation Shanghai Jiao Tong University Shanghai China and CIAM and ACCESS Centers Royal Institute of Technology Stockholm Sweden

Given a circular probability density function, called the true probability density function, the goal is to find a Dirac mixture approximation based on some circular moments of the true density. When keeping the locations of the Dirac points fixed, but almost arbitrarily located, we are applying recent results on the circulant rational covariance extension problem to the problem of calculating the weights. For the case of simultaneously calculating optimal locations, additional constraints have to be deduced from the given density. For that purpose, a distance measure for the deviation of the Dirac mixture approximation from the true density is derived, which then is minimized while considering the moment conditions as constraints. The method is based on progressive numerical minimization, converges quickly and gives well- distributed Dirac mixtures that fulfill the constraints, i.e., have the desired circular moments.

关键词： Circular densities Dirac mixture approximation moment problem

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Bio-inspired falling motion control for a biped humanoid robot

Bio-inspired falling motion control for a biped humanoid rob...

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IEEE-RAS International Conference on Humanoid Robots

作者： Gan Ma Qiang Huang Zhangguo Yu Xuechao Chen Kenji Hashimoto Atsuo Takanishi Yun-Hui Liu Ministry of Education Key Laboratory of Biomimetic Robots and Systems China Intelligent Robotics Institute Beijing Institute of Technology Beijing China Humanoid Robotics Institute Waseda University Tokyo Japan The Department of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

ISBN: (纸本)9781479971756

Although consistent stability is desirable, a biped humanoid robot encounters a high risk of falling. Such falls may cause serious damage to both the robot and the environment. This study focuses on this issue and investigates four strategies based on human protective falling motion. These strategies are: "knee flexion", "torso flexion forward", "torso translation backward" and "knee stretched". First, the effectiveness of the strategies for the safe landing is analyzed from an energy variation perspective of the robot system. The four strategies are used to do negative work that reduced the energy of the robot system, thereby reducing the impact velocity of the robot. Then, a simulation study on a human-sized humanoid robot is conducted to assess the influence of the strategies on safe landing. Finally, based on the simulation results for each strategy, a safe falling motion control method is proposed and validated through simulation.

关键词： Torso Humanoid robots Knee Mechanical energy Force Mathematical model

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Tuning the position of a fuzzy cognitive map attractor using backpropagation through time

Tuning the position of a fuzzy cognitive map attractor using...

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7th International Conference on Integrated Modeling and Analysis in Applied Control and automation, IMAACA 2013, Held at the International Multidisciplinary Modeling and Simulation Multiconference, I3M 2013

作者： Gregor, Michal Groumpos, Peter P. Department of Control and Information Systems Faculty of Electrical Engineering University of Žilina Slovakia Laboratory for Automation and Robotics Department of Electrical and Computer Engineering University of Patras Greece

ISBN: (纸本)9781629934884

The paper proposes a new learning method for fuzzy cognitive maps, which makes it possible to encode an attractor into the map. The method is based on the principle of backpropagation through time known from the theory of artificial neural networks. Simulation results are presented to show how well the method performs. It is shown that the results are superior to those achieved using Hebbian learning approaches such as nonlinear Hebbian learning. Some lines for possible future research and development are given.

关键词： Fuzzy Cognitive Maps

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An enhancement in conventional potential field using a fuzzy system for navigation of a sumo robot

An enhancement in conventional potential field using a fuzzy...

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2013 16th International Conference on Advanced robotics, ICAR 2013

作者： Lima, Carlos Erlan Olival De Araújo, Francisco Marcelino Almeida Da Silva Jr., Mário Bibiano Rocha Filho, Antônio Edson Rabêlo, Ricardo De Andrade Lira Da Silva, Thiago Allisson Ribeiro De Oliveira Alves, Antonio Jose LABoratory of Intelligent Robotics Automation and Systems - LABIRAS CAPES Foundation Brasilia - DF ZIP CODE 70.040-020 Brazil Instituto Federal Do Piauí - IFPI Tianjin University Teresina Brazil LABoratory of Intelligent Robotics Automation and Systems - LABIRAS Instituto Federal Do Piauí - IFPI Teresina Brazil Computing Department Universidade Federal Do Piaui - UFPI Teresina Brazil

ISBN: (纸本)9781479927227

An enhancement in conventional potential field is presented in this paper for autonomous sumo robot class navigation with dynamic environments including moving target and static obstacle. This method determines the velocity and the path taken by the robot in order to reach your target in the shortest time possible. This improvement on the conventional potential field is used to determine the velocity and position of an autonomous sumo robot class, which is intended to push the opponent out of the arena. This hybrid method is composed of potential field approach with fuzzy logic, and in this study the Mamdani model is used to obtain the necessary variables to determine the velocity and direction of the robot. Two fuzzy systems are used, both with three inputs and one output. The only difference between the two fuzzy systems is the number of linguistics terms. One simulation has been done in the MATLAB to verify the enhancement of the hybrid method in relation to the conventional potential field. The simulation represents the trajectory of the robot until find the target. Accordingly with the simulation done, the hybrid method was 14% more effective. © 2013 IEEE.

关键词： Fuzzy systems

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Velocity and direction planning in a sumo robot type using the method of potential field with fuzzy systems

Velocity and direction planning in a sumo robot type using t...

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2013 16th International Conference on Advanced robotics, ICAR 2013

作者： Lima, Carlos Erlan Olival De Araújo, Francisco Marcelino Almeida Da Silva Jr., Mário Bibiano Rocha Filho, Antônio Edson De Andrade Lira Rabêlo, Ricardo Da Silva, Thiago Allison Ribeiro De Oliveira Alves, Antonio Jose LABoratory of Intelligent Robotics Automation and Systems - LABIRAS CAPES Foundation Ministry of Education of Brazil Brasilia - DF ZIP CODE 70.040-020 Brazil Instituto Federal Do Piauí - IFPI Tianjin University Teresina Brazil LABoratory of Intelligent Robotics Automation and Systems - LABIRAS Instituto Federal Do Piauí - IFPI Teresina Brazil Computing Department Universidade Federal Do Piaui - UFPI Teresina Brazil

ISBN: (纸本)9781479927227

An application of the potential field method is presented in this paper for autonomous sumo robot class navigation with dynamic environments including moving target and static obstacle. The method used in this paper aims to planning the velocity and the direction taken by the robot in order to reach your target in the possible shortest time. The design velocity is determined from the relative velocities between the robot and the target as well as the relative positions between them. This work uses a hybrid method to determine the velocity and position of a sumo robot class, which is intended to push the opponent out of the arena. This hybrid method applies the potential field with fuzzy logic and use the Mamdani model to obtain the necessary variables for determining the velocity and direction to be followed by the robot. For determining the time necessary to find the target two simulations were done in the MATLAB. The obtained results show that the hybrid method overcomes the local minimum problem within any stationary or dynamic environment with static obstacles. © 2013 IEEE.

关键词： Velocity

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