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SAI Intelligent Systems Conference (IntelliSys)

作者： Bojan Jerbic Tomislav Stipancic Tomislav Tomasic Dept. of Robotics and Production System Automation Faculty of Mechanical Engineering and Naval Architecture Zagreb Croatia Institute for Nuclear Technology Zagreb Croatia

This paper describes an approach in which a robot is using a virtual or inner representation of its own body to ensure a safe and efficient interaction within the physical world. By analysing correlations within its surroundings, the robot is able to plan task-oriented and socially accepting responses. This approach is inspired by the phenomenon called bodily awareness, which is found in humans. Compared to conventional approaches where robots are preprogramed to react on finite number of environmental occurrences or states, the proposed approach gives the robot an ability to adapt to changes through a constant interaction. To achieve this, a robot interaction space is discretized and constantly analysed. As a part of the new cognitive model, a virtualized image of the robot body is used to avoid all possible collisions. The model also contains a probabilistic component to provide the most appropriate solution to given environmental conditions where the environment is naturally highly dynamic and unpredictable.

关键词： Robot kinematics Collision avoidance Robot sensing systems Service robots Computational modeling Three-dimensional displays

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Performance of BPSK and BFSK digital modulation schemes in colored noise scenario

Performance of BPSK and BFSK digital modulation schemes in c...

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International Symposium on Underwater Technology

作者： Bipin Kumar Patel Dibbendu Roy Siva Ram Krishna Vadali Robotics & Automation Division CSIR-CMERI Durgapur Dept. of Electronics & Communication Engineering NIT Durgapur Council of Scientific & Industrial Research New Delhi Delhi IN

It is well known that the underwater channel is a hostile environment for data transmission. In this work we compute the link budget for a passive sonar link for a targeted specification and subsequently present a simulation study of the performance of two digital modulation techniques, (BPSK and BFSK) over an underwater acoustic channel. A BER performance comparison on the two modulation schemes concludes the paper.

关键词： Noise Frequency shift keying Bit error rate Mathematical model Sonar Propagation losses Baseband

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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 real-time dynamic gesture recognition based on 3D trajectories in distinguishing similar gestures

A real-time dynamic gesture recognition based on 3D trajecto...

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International Conference on Information and automation (ICIA)

作者： Zeyu Ding Zexiong Zhang Yanmei Chen Yen-Lun Chen Xinyu Wu University of Science and Technology of China Guangdong Provincial Key Laboratory of Robotics and Intelligent System Chinese Academy of Sciences Dept. Mechanical and Automation Engineering The Chinese University of Hong Kong

There are many shape-similar gestures which cause errors in the process of hand gesture recognition. In this paper, a new method which can distinguish the similar gestures was proposed. The information of motion trajectory is captured by a leap motion in three-dimension space, and the orientation characteristics are quantified and coded as the feature. Then the Hidden Markov Model (HMM) algorithm is utilized to model and classify gestures. But there are many shape-similar gestures in our database (numbers 0-9 and alphabets A-Z) such as S and 5, Z and 2 whose recognition rates are low. In this paper, we proposed a new method that can distinguish the similar gestures in real-time. The experiment result demonstrates the effectiveness of the proposed method.

关键词： Hidden Markov models Feature extraction Gesture recognition Trajectory Real-time systems Three-dimensional displays Accuracy

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Development of one-channel fNIRS system and physiological noise reduction in brain hemodynamic responses

Development of one-channel fNIRS system and physiological no...

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IEEE International Conference on robotics and Biomimetics

作者： Xuxian Yin Gang Shi Zhidong Wang Hongyi Li State Key Laboratory of Robotics Shenyang Institute of Automation (SIA) Chinese Academy of Sciences (CAS) Shenyang 110016 P. R. China and University of Chinese Academy of Sciences Beijing 100049 P. R. China State Key Laboratory of Robotics Shenyang Institute of Automation (SIA) Chinese Academy of Sciences (CAS) Shenyang 110016 P. R. China State Key Laboratory of Robotics Shenyang Institute of Automation (SIA) Chinese Academy of Sciences (CAS) Shenyang 110016 P. R. China and Dept. of Advanced Robotics Chiba Institute of Technology Chiba 2750016 Japan State Key Laboratory of Robotics Shenyang Institute of Automation (SIA) Chinese Academy of Sciences (CAS) Shenyang 110016 P. R. China and School of Mechanical Engineering & Automation Northeastern University Shenyang China

ISBN: (纸本)9781467396769

Functional near-infrared spectroscopy (fNIRS) is an emerging non-invasive optical technique which can measure cortical brain activities. This study describes the development of one-channel fNIRS system designed for brain-computer interface (BCI), six subjects participate in the experiment, the concentration changes of oxy-hemoglobin (HbO_2) and deoxy-hemoglobin (Hb) during mental arithmetic task are measured. And physiological noise in hemodynamic responses are reduced based on empirical mode decomposition (EMD). EMD is a data-driven and adaptive algorithm for analyzing non-stationary data. This method decomposes the original data into a set of intrinsic mode functions (IMFs). Noise can be eliminated by selecting appropriate IMFs. Compared with conventional butterworth filter, EMD achieves a higher contrast to noise ratio (CNR) in physiological noise reduction.

关键词： fNIRS BCI CNR

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Application of hierarchical systems technology in conceptual design of biomechatronic system

Application of hierarchical systems technology in conceptual...

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International Conference on Systems Science, ICSS 2013

作者： Miatliuk, Kanstantsin Kim, Yoon Hyuk Bialystok University of Technology Dept. of Automation and Robotics Wiejska 45C Bialystok15-351 Poland Kyung Hee University School of Engineering Yongin446-701 Korea Republic of

ISBN: (纸本)9783319018560

Application of cybernetic technology of conceptual design of biomechatronic surgical robotics system (SRS) originated by systems theory is suggested in the paper. Traditional models of artificial intelligence and mathematics do not allow describing biomechatronic systems being designed on all its levels in one common formal basis, i.e. they do not give connected descriptions of the systems structure, the system as dynamic unit in its environment and the environment construction. To avoid this drawback, the technology of hierarchical and dynamic systems was chosen as a theoretical means for conceptual design and control tasks performing. Furthermore, in comparison with traditional methods the proposed technology gives the description of connected electronic, mechanical, biological, human-machine and computer subsystems of biomechatronic object in common formal basis. Theoretical basis of the coordination technology is briefly considered first. The example of the technology realization in conceptual design of SRS is presented after that in the paper. © Springer International Publishing Switzerland 2014.

关键词： Hierarchical systems

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Kinematic modeling and control of a multi-joint soft inflatable robot arm with cable-driven mechanism

Kinematic modeling and control of a multi-joint soft inflata...

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2014 IEEE International Conference on robotics and automation, ICRA 2014

作者： Qi, Ronghuai Lam, Tin Lun Xu, Yangsheng Intelligent Robotics Research Centre Smart China Research Smart China Holdings Limited Shatin N.T. Hong Kong Dept. of Mechanical and Automation Engineering Chinese University of Hong Kong Shatin N.T. Hong Kong

In this paper, the kinematic modeling and control for a multi-joint inflatable robot arm with cable-driven mechanism are proposed. The soft inflatable robot arm is capable of imitating human arms to realize remote interaction. The weight of the arm is only about 50 grams, and collision safe. To solve the challenge problems of kinematics of the soft inflatable arm, new approaches are proposed, including redundant rigid arm and soft inflatable joint models. The approaches have a good advantage of applying to muti-joint arms. As our knowledge it is the first time to solve the kinematics of muti-joint soft inflatable arm in Three-Dimensional coordinate space. Numerous experiments have been conducted, including movement space and positioning accuracy. The workspace and velocity are close to an adult's arm movement space and normal motion speed. © 2014 IEEE.

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Design and implementation of a low-cost and lightweight inflatable robot finger

Design and implementation of a low-cost and lightweight infl...

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2014 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Ronghuai Qi Tin Lun Lam Yangsheng Xu Smart China Research Intelligent Robotics Research Centre Hong Kong Dept. of Mechanical and Automation Engineering The Chinese University of Hong Kong Hong Kong

In this paper, mechanical design and implementation of a low-cost and lightweight inflatable robot finger are proposed. The proposed soft inflatable robot finger is different from traditional designs. It uses a common and low cost inflatable material and can be easily and massively manufactured. The proposed soft inflatable finger only weighs 0.8 grams, but can well realize swift movement which is actuated by low pressure air. Numerous analyses and experiments have been conducted for key parameters selection of the mechanical design. The performances of the proposed finger including flexing and extending have also been evaluated, and results are satisfactory.

关键词： Robots Strain Grippers Fingers Plastics Rubber

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Unified hysteresis and creep compensation in AFM tip positioning with an extended PI model

Unified hysteresis and creep compensation in AFM tip positio...

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IEEE International Conference on robotics and automation (ICRA)

作者： Zhiyu Wang Lianqing Liu Zhidong Wang Wenxue Wang Dept. of Advanced Robotics Chiba Institute of Technology Japan State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences (CAS) China College of Electrical and Control Engineering Liaoning Technical University and University of Chinese Academy of Sciences China

The nonlinearities such as hysteresis and creep are the major factors inherent in PZT actuation that affect the tip positioning precision and manipulation performance of the AFM system. In this study, an extended PI model is generalized by introducing a creep model to the basic hysteretic operator of the PI model at the inflexion point of the hysteresis loop. Unified compensation for hysteresis and creep can be implemented with the extended PI model. Experiment results demonstrate the validity and effectiveness of the extended PI model and it is implied that the inflexion creep compensation not only improves the tip positioning precision at the inflexion points on the hysteresis loops, but also the localization effectiveness during the whole process of PZT actuation.

关键词： Creep Hysteresis Computational modeling Mathematical model Calibration Trajectory Load modeling

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Kinematic modeling and control of a multi-joint soft inflatable robot arm with cable-driven mechanism

Kinematic modeling and control of a multi-joint soft inflata...

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IEEE International Conference on robotics and automation (ICRA)

作者： Ronghuai Qi Tin Lun Lam Yangsheng Xu Intelligent Robotics Research Centre Smart China Research Smart China Holdings Limited Shatin Hong Kong Dept. of Mechanical and Automation Engineering The Chinese University of Hong Kong Shatin Hong Kong

关键词： Joints Kinematics Robot kinematics Shoulder Elbow Electron tubes

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