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Microscopic image segmentation using quantum inspired evolutionary algorithm

Journal of Advanced Microscopy Research 2015年第3期10卷 164-173页

作者： Choudhury, Alokeparna Samanta, Sourav Dey, Nilanjan Ashour, Amira S. Balas-Timar, Dana Gospodinov, Mitko Gospodinova, Evgeniya Department of Computer Science and Engineering University Institute of Technology Burdwan West Bengal713104 India Department of Information Technology Techno India College of Technology Kolkata700156 India Department of Electronics and Electrical Communications Engineering Faculty of Engineering Tanta University 31527 Egypt Aurel Vlaicu University of Arad Arad310130 Romania Institute of Systems Engineering and Robotics Bulgarian Academy of Sciences Sofia1113 Bulgaria

Image segmentation has became an important research area for various medical imaging fields. The automated complex analytical process makes it a huge time consuming procedure. The intention to microscopic images segmentation is to extract the cellular, nuclear or tissue components. This is considered a challenging process due to the large variations of features of these components (size, shape, orientation or texture). In this paper, a novel approach to deal with rats' microscopic hippocampus images segmentation based on the hybrid evolutionary strategy (ES) is proposed. The proposed work used the quantum-inspired evolutionary algorithm (QIEA) to establish the optimal level for the multilevel thresholding. The QIEA depends on both quantum and evolutionary computing. An intensive works for automatic hippocampus segmentation is performed on a database of 179 images. The acquired results have demonstrated that the proposed algorithm provides superior segmentation with eight levels (L = 8), that offer the highest correlation between the original and the corresponding segmented image. © Copyright 2015 American Scientific Publishers All rights reserved.

关键词： Evolutionary algorithms

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Automatic and robust single-camera specular highlight removal in cardiac images

Automatic and robust single-camera specular highlight remova...

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

作者： Samar M. Alsaleh Angelica I. Aviles Pilar Sobrevilla Alicia Casals James K. Hahn Department of Computer Science George Washington University Washington DC U.S.A. Intelligent Robotics and Systems Group Universitat Politecnica de Cataluya Barcelona Spain Department of Applied Mathematics II Universitat Politecnica de Cataluya Barcelona Spain Institute for Bioengineering of Catalonia Universitat Politecnica de Cataluya Barcelona Spain

In computer-assisted beating heart surgeries, accurate tracking of the heart's motion is of huge importance and there is a continuous need to eliminate any source of error that might disturb the tracking process. One source of error is the specular reflection that appears on the glossy surface of the heart. In this paper, we propose a robust solution for the detection and removal of specular highlights. A hybrid color attributes and wavelet based edge projection approach is applied to accurately identify the affected regions. These regions are then recovered using a dynamic search-based inpainting with adaptive windowing. Experimental results demonstrate the precision and efficiency of the proposed method. Moreover, it has a real-time performance and can be generalized to various other applications.

关键词： Image color analysis Heart Image edge detection Wavelet transforms Surgery Tracking

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Force-feedback sensory substitution using supervised recurrent learning for robotic-assisted surgery

Force-feedback sensory substitution using supervised recurre...

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

作者： Angelica I. Aviles Samar M. Alsaleh Pilar Sobrevilla Alicia Casals Intelligent Robotics and Systems Group Universitat Politecnica de Cataluya Barcelona Spain Department of Computer Science George Washington University Washington DC U.S.A. Department of Applied Mathematics II Universitat Politecnica de Cataluya Barcelona Spain Institute for Bioengineering of Catalonia Universitat Politecnica de Cataluya Barcelona Spain

The lack of force feedback is considered one of the major limitations in Robot Assisted Minimally Invasive Surgeries. Since add-on sensors are not a practical solution for clinical environments, in this paper we present a force estimation approach that starts with the reconstruction of a 3D deformation structure of the tissue surface by minimizing an energy functional. A Recurrent Neural Network-Long Short Term Memory (RNN-LSTM) based architecture is then presented to accurately estimate the applied forces. According to the results, our solution offers long-term stability and shows a significant percentage of accuracy improvement, ranging from about 54% to 78%, over existing approaches.

关键词： computer architecture Microprocessors Force Surgery Robot sensing systems Estimation

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SocialRobot: An Interactive Mobile Robot for Elderly Home Care

SocialRobot: An Interactive Mobile Robot for Elderly Home Ca...

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IEEE/SICE International Symposium on System Integration

作者： David Portugal Luis Santos Paulo Alvito Jorge Dias George Samaras Eleni Christodoulou CiTARD Services Ltd. Institute of Systems and Robotics University of Coimbra IDMind - Engenharia de Sistemas Lda. George Samaras is with the Department of Computer Science University of Cyprus

ISBN: (纸本)9781467372435

SocialRobot is a collaborative European project, which focuses on providing a practical and interactive robotic solution to improve the quality of life of elderly people. Having this in mind, a state of the art mobile robot platform has been integrated with virtual social care technology to meet the elderly individual needs and requirements, following a human centered approach. In this paper, we make an overview of SocialRobot, addressing mainly the integration of the platform and the architecture developed for the project, as well as the existing robot services, the human-robot interactive scenarios prepared, and results extracted from experimental tests with the mobile robot platform.

关键词： Robot sensing systems Senior citizens Mobile robots Collision avoidance Safety Robot kinematics

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Opening remarks

2016 International Conference on Advances in Human Machine I...

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2016 International Conference on Advances in Human Machine Interaction, HMI 2016 2016年

作者： Nagaraja, Ch. Swamy, J. Nagendra Rajendra, J. Khan, M.S. Vishwanath Reddy, D.S. Manjunath, N. Dillmann, Ruediger Tarn, Tzyh Jong Zhao, Qianchuan Ammi, Mehdi Zuberek, Wlodek M. Sandhu, P.S. Patthira Newman, K. De Silva Liyanage, Chandratilak Hassan, Sohair Aly Aly Sun, Kien Wen Rahman, Md. Moshiur Ordoño, E. Evangelista Sharma, R.K. Mishra, Preeti Chandel, B.S. Singla, Ekta Petric, Tadej Zhong, Yu Jiglar, Janson Alemzadeh, Kazem Asokan, T. Tripathi, Animesh Tripathi, Manoj Ram, Swaminath Shrma, M.K. Panday, P.N. Kumar, Devendra Hinchey, Mike Stilman, Boris Suraj, Zbigniew Pal, Sankar K. Sasi, Sreela Rajan, Deepu Marshall, Roger G. Abraham, Ajith Peter S, David Paul, Vargheese Gopakumar, V. Dustdar, Schahram Soto, Sebastián Ventura Rausch, Andreas Angelis, Lefteris Nelson, Andrew L. Botzheim, Janos Bernardino, Heder Soares Zboril, Frantisek Ane, Bernadetta Kwintiana Maeda, Toshiyuki Sakalauskas, Virgilijus Hann, Garenth Lim King Samek, Jan Romero Salguero, José Raúl Varghese, Kuruvilla Kriksciuniene, Dalia Mathew, Jimson Reif, Wolfgang Mauri, Giancarlo Cabrerizo Lorite, Francisco Javier Özcan, Ender Cho, Sung-Bae Paily, Roy P. Rezankova, Hana Tudjarov, Boris Hong, Wei-Chiang De Oliveira, José Valente Flores Romero, Juan Jose Oskouei, Rozita Jamili Cicchetti, Antonio Roy, Chanchal Segura, Sergio Samuel, C. Mallet, Frédéric Mernik, Marjan Punnekkat, Sasikumar Waseemulla, A. Sri Devaraj Urs Educational Trust Bangalore India R. L. Jalappa Institute of Technology Doddaballapur Bangalore India Humanoids and Intelligence Systems Lab Kalsruhe Germany Electrical and Systems Engineering Washington University in St. Louis United States Deputy Director of Center for Intelligent and Networked Systems Department of Automation Tsinghua University Beijing China Department of Computer Science CNRS/LIMSI Lab AMI Group France Memorial University St. John'sNL Canada RBIT and Bio-Technology India LR University Thailand University of Colorado at Boulder Boulder United States Faculty of Science University of Brunei Brunei University of Kuala Lumpur Malaysia National Chiao Tung University Taiwan EPR Centre Bangladesh Mapua Institute of Technology Philippines ARO CWC Lucknow India Mpec Kanpur India DSC DBS Kanpu India Indian Institute of Technology Ropar India Jozaf Stefan Institute Department of Automation Biocyernetics and Robotics Ljubljana Slovenia Robotics Institute Carnegie Mellon University Pittsburgh United States Faculty of Engineering University of Bristol United Kingdom Department of Engineering Design Indian Institute of Technology Madras India Lucknow Uni Lucknow India CSJM Uni Kanpur India UPPCB Lucknow India PCB Roorkee India Awadh Uni Faijabad India Agra Uni Agra India Lero University of Limerick Ireland University of Colorado Denver United States University of Rzeszow Poland Indian Statistical Institute Kolkata India Gannon University PA United States Nanyang Technical University Singapore Singapore Plymouth State University NH United States MIR Labs United States Cochin University of Science and Technology India State Project Facilitation Unit TEQIP Kerala India Technical University of Vienna Austria University of Cordoba Spain Clausthal University of Technology Germany Aristotle University of Thessaloniki Greece Androtics LLC TucsonAZ United States Tokyo Metropolitan University Japan Federal Unive

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Latent space policy search for robotics

Latent space policy search for robotics

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2014 IEEE/RSJ International Conference on Intelligent Robots and systems, IROS 2014

作者： Luck, Kevin Sebastian Neumann, Gerhard Berger, Erik Peters, Jan Amor, Heni Ben Department of Computer Science Technische Universität Darmstadt Darmstadt64289 Germany Department of Mathematics and Computer Science Technische Universität Bergakademie Freiberg Freiberg09599 Germany Institute for Robotics and Intelligent Machines Georgia Institute of Technology GA30332 United States Max Planck Institute for Intelligent Systems Tübingen72076 Germany

ISBN: (纸本)9781479969340

Learning motor skills for robots is a hard task. In particular, a high number of degrees-of-freedom in the robot can pose serious challenges to existing reinforcement learning methods, since it leads to a high-dimensional search space. However, complex robots are often intrinsically redundant systems and, therefore, can be controlled using a latent manifold of much smaller dimensionality. In this paper, we present a novel policy search method that performs efficient reinforcement learning by uncovering the low-dimensional latent space of actuator redundancies. In contrast to previous attempts at combining reinforcement learning and dimensionality reduction, our approach does not perform dimensionality reduction as a preprocessing step but naturally combines it with policy search. Our evaluations show that the new approach outperforms existing algorithms for learning motor skills with high-dimensional robots. © 2014 IEEE.

关键词： Reinforcement learning

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Control Strategies for a Humanoid Robot to Drive and then Egress a Utility Vehicle for Remote Approach

Control Strategies for a Humanoid Robot to Drive and then Eg...

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IEEE-RAS International Conference on Humanoid Robots

作者： Hyobin Jeong Jaesung Oh Mingeuk Kim Kyungdon Joo In So Kweon Jun-Ho Oh Humanoid Research Center School of Mechanical Aerospace & Systems Engineering Department of Mechanical Engineering Korea Advanced Institute of Science and Technology Robotics and Computer Vision Laboratory School of Mechanical Aerospace & Systems Engineering Department of Electrical Engineering Korea Advanced Institute of Science and Technology Department of Electrical Engineering KAIST

ISBN: (纸本)9781479968862

This paper proposes strategies for the driving and egress of a vehicle with a humanoid robot. To drive the vehicle, the RANSAC method was used to detect obstacles, and the Wagon model was used to control the steering and velocity of the vehicle with only a limited number of sensors which were installed on the humanoid robot. Additionally, a manual teleoperating method was used with the lane projection technique. For the egress motion, gain override and the Cartesian position/force control technique were used to interact with the vehicle structure. To overcome the disadvantages of a highly geared manipulator, a special technique was used that included modelled friction compensation and a non-complementary switching mode. DRC-HUBO+ used the proposed method to perform a vehicle driving and egress task in the DRC finals 2015.

关键词： Humanoid robots EGRESS vehicle Vehicle driving Automobile driving UTILITY VEHICLES control strategy friction compensation DRIVES Steering

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On the approximate period problem

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IAENG International Journal of Applied Mathematics 2014年第1期44卷 1-9页

作者： Gorbenko, Anna Ural Federal University Department of Intelligent Systems and Robotics of Mathematics and Computer Science Institute 620083 Ekaterinburg Russia

Different regularities can be used to identify the sequence among other sequences. Regularities allow us to infer an information about the evolution of the sequence. Tandem repeats are the most frequent in the genomes of eukaryotes. Extraction of regularities is a widely studied problem. However, searching for exact tandem repeats can be too restrictive. So, a natural extension of the repetition is to allow errors. In this paper, we consider the approximate period problem. In particular, we consider an explicit reduction from the approximate period problem to the satisfiability problem and present experimental results for different satisfiability algorithms. Also, we consider the approximate period problem for sequences of motor primitives of robots. In particular, we use the approximate period problem to obtain some meta-parameters that adapt the global motion behavior. We try to use such metaparameters for learning to generalize motor primitives to a different behavior by trial and error without re-learning the task.

关键词： Genetic algorithms

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The discrete minimum constraint removal motion planning problem

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AIP Conference Proceedings 2015年第1期1648卷

作者： Anna Gorbenko Vladimir Popov Ural Federal University Department of Intelligent Systems and Robotics Mathematics and Computer Science Institute Lenin st. 51 620083 Ekaterinburg Russian Federation

Many planning problems for robots are of considerable interest. In this paper, we consider the discrete minimum constraint removal motion planning problem that can be used for a motion planning formulation with explanations for failure. We consider an efficient approach to solve the problem. In particular, we consider an explicit reduction from the decision version of the problem to the satisfiability problem. We present the results of computational experiments for different satisfiability algorithms.

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The problem of robot swarms control with only global signals

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AIP Conference Proceedings 2015年第1期1648卷

Problems of swarm robotics are extensively studied in contemporary robotics. In this paper, we consider the problem of robot swarms control with only global signals. We propose an efficient approach to solve the problem. In particular, we consider an explicit reduction from the decision version of the problem to the satisfiability problem. For different satisfiability algorithms, we present the results of computational experiments.

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