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Generalized Norm Optimal Iterative Learning Control with Intermediate Point and Sub-interval Tracking

International Journal of Automation and computing 2015年第3期12卷 243-253页

作者： David H.Owens Chris T.Freeman Bing Chu Department of Automatic Control and Systems Engineering University of Sheffield School of Electronics and Computer Science University of Southampton Advanced Robotics Division Italian Institute of Technology

Norm optimal iterative learning control(NOILC) has recently been applied to iterative learning control(ILC) problems in which tracking is only required at a subset of isolated time points along the trial duration. This problem addresses the practical needs of many applications, including industrial automation, crane control, satellite positioning and motion control within a medical stroke rehabilitation context. This paper provides a substantial generalization of this framework by providing a solution to the problem of convergence at intermediate points with simultaneous tracking of subsets of outputs to reference trajectories on subintervals. This formulation enables the NOILC paradigm to tackle tasks which mix "point to point" movements with linear tracking requirements and hence substantially broadens the application domain to include automation tasks which include welding or cutting movements, or human motion control where the movement is restricted by the task to straight line and/or planar segments. A solution to the problem is presented in the framework of NOILC and inherits NOILC s well-defined convergence properties. Design guidelines and supporting experimental results are included.

关键词： Iterative learning control learning control optimization linear systems robotics.

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Detection and retargeting of emphasized text for content summarization

Detection and retargeting of emphasized text for content sum...

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International Conference on Advances in Computing, Communications and Informatics (ICACCI)

作者： Md. Ajij Sanjoy Pratihar Kanishka Ganguly Computer Science and Engineering Department National Institute of Technology Meghalaya Shillong India Maryland Robotics Center University of Maryland College Park MD USA

ISBN: (纸本)9781509020300

In this paper, we propose a simple and robust algorithm for detection and retargeting of emphasized words, written as italics, in a scanned document page. The detection of italics is done using an appropriate use of Principal Component Analysis (PCA), applied on a selected subset of pixels coming from the input character image boundary. The proposed method is font and style invariant. The localization of the emphasized words helps us in information retrieval by means of retargeted words. It is seen that, a good number of publication houses use emphasized (italic) words for specifying the keywords, author's affiliations etc., in the front page of the articles. Our method extracts and retargets the emphasized words to summarize the content of the papers. Experimental result shows the robustness and degree of precision.

关键词： Image edge detection Principal component analysis Information retrieval Informatics Robustness Indexes Image segmentation

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Dynamics and control of separable coupled rigid body systems

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robotics and biomimetics 2017年第1期4卷 14页

作者： Kinda Khalaf Dongming Gan Hooshang Hemami Department of Biomedical Engineering Khalifa University of Science and Technology Abu Dhabi UAE. Robotics Institute/Mechanical Engineering Department Khalifa University of Science and Technology Abu Dhabi UAE. Department of Electrical and Computer Engineering The Ohio State University Columbus OH 43210 USA.

This paper explores the dynamics of separable coupled rigid body systems, a special class of constrained rigid body systems. These are defined as two systems that interact with each other by forces of contact, resulting in a reduction in dimensionality and complexity. The mechanics and consequences of this reduction are investigated here. The basic hypothesis and an example of the reduction in two successive steps are formulated. A simple mechanical biped model is developed and analyzed in some details by both system theoretical concepts and simulations. The main contribution of this work is the novel extension to the known dynamics of constrained rigid bodies. The modular, versatile and systematic formulation presented here is computationally efficient and has many applications in the studies of the human neuro-musculoskeletal system, robotic systems and humanoids, as well as clinical and sports biomechanics applications. computer simulations are provided to demonstrate the feasibility and effectiveness of the methodology.

关键词： Constrained dynamics Control Coupled mechanical systems Dimensionality reduction Kinematics

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DAC-h3: A proactive robot cognitive architecture to acquire and express knowledge about the world and the self

arXiv

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arXiv 2017年

作者： Moulin-Frier, Clément Fischer, Tobias Petit, Maxime Pointeau, Grégoire Puigbo, Jordi-Ysard Pattacini, Ugo Low, Sock Ching Camilleri, Daniel Nguyen, Phuong Hoffmann, Matej Chang, Hyung Jin Zambelli, Martina Mealier, Anne-Laure Damianou, Andreas Metta, Giorgio Prescott, Tony J. Demiris, Yiannis Dominey, Peter Ford Verschure, Paul F.M.J. Laboratory for Synthetic Perceptive Emotive and Cognitive Systems Universitat Pompeu Fabra Barcelona08002 Spain Barcelona Spain Personal Robotics Laboratory Department of Electrical and Electronic Engineering Imperial College London SW7 2AZ United Kingdom Robot Cognition Laboratory INSERM U846 Stem Cell and Brain Research Institute Bron69675 France Italian Institute of Technology iCub Facility Via Morego 30 Genova Italy Department of Cybernetics Faculty of Electrical Engineering Czech Technical University in Prague Department of Computer Science University of Sheffield United Kingdom

This paper introduces a cognitive architecture for a humanoid robot to engage in a proactive, mixed-initiative exploration and manipulation of its environment, where the initiative can originate from both the human and the robot. The framework, based on a biologically-grounded theory of the brain and mind, integrates a reactive interaction engine, a number of state-of-the art perceptual and motor learning algorithms, as well as planning abilities and an autobiographical memory. The architecture as a whole drives the robot behavior to solve the symbol grounding problem, acquire language capabilities, execute goal-oriented behavior, and express a verbal narrative of its own experience in the world. We validate our approach in human-robot interaction experiments with the iCub humanoid robot, showing that the proposed cognitive architecture can be applied in real time within a realistic scenario and that it can be used with naive users. Copyright © 2017, The Authors. All rights reserved.

关键词： Human robot interaction

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Distributed knowledge leader selection for multi-robot environmental sampling under bandwidth constraints

Distributed knowledge leader selection for multi-robot envir...

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IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Wenhao Luo Shehzaman S. Khatib Sasanka Nagavalli Nilanjan Chakraborty Katia Sycara Robotics Institute School of Computer Science Carnegie Mellon University Pittsburgh Pennsylvania USA Department of Mechanical Engineering Stony Brook University New York USA

ISBN: (纸本)9781509037636

In many multi-robot applications such as target search, environmental monitoring and reconnaissance, the multi-robot system operates semi-autonomously, but under the supervision of a remote human who monitors task progress. In these applications, each robot collects a large amount of task-specific data that must be sent to the human periodically to keep the human aware of task progress. It is often the case that the human-robot communication links are extremely bandwidth constrained and/or have significantly higher latency than inter-robot communication links, so it is impossible for all robots to send their task-specific data together. Thus, only a subset of robots, which we call the knowledge leaders, can send their data at a time. In this paper, we study the knowledge leader selection problem, where the goal is to select a subset of robots with a given cardinality that transmits the most informative task-specific data for the human. We prove that the knowledge leader selection is a submodular function maximization problem under explicit conditions and present a novel distributed submodular optimization algorithm that has the same approximation guarantees as the centralized greedy algorithm. The effectiveness of our approach is demonstrated using numerical simulations.

关键词： Robot sensing systems Robot kinematics Optimization Greedy algorithms Data models

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Semantic video annotation for accessible resources in flipped classrooms 21

Semantic video annotation for accessible resources in flippe...

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21st International Conference on Distributed Multimedia Systems, DMS 2015

作者： Torre, Ilaria Vercelli, Gianni Department of Computer Science Bioengineering Robotics and Systems Engineering University of Genoa Italy

In this paper we present a project for applying a framework for accessibility to educational activities in flipped classrooms by exploiting semantic video annotation. The framework exploits semantic and adaptive techn... 详细信息

ISBN: (纸本)1891706381

关键词： Internet of things

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Surgical data science: Enabling next-generation surgery

arXiv

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arXiv 2017年

作者： Maier-Hein, Lena Vedula, Swaroop Speidel, Stefanie Navab, Nassir Kikinis, Ron Park, Adrian Eisenmann, Matthias Feussner, Hubertus Forestier, Germain Giannarou, Stamatia Hashizume, Makoto Katic, Darko Kenngott, Hannes Kranzfelder, Michael Malpani, Anand März, Keno Neumuth, Thomas Padoy, Nicolas Pugh, Carla Schoch, Nicolai Stoyanov, Danail Taylor, Russell Wagner, Martin Hager, Gregory D. Jannin, Pierre Heidelberg Germany Malone Center for Engineering in Healthcare Johns Hopkins University BaltimoreMD United States Institute for Anthropomatics and Robotics Karlsruhe Institute of Technology Karlsruhe Germany Chair for Computer Aided Medical Procedures Technical University of Munich Munich Germany Department of Radiology Brigham and Women’s Hospital Harvard Medical School BostonMA United States Department of Computer Science University of Bremen Bremen Germany Fraunhofer MEVIS Bremen Germany Department of Surgery Center of Anne Arundel Health System AnnapolisMD United States Department of Surgery Klinikum rechts der Isar Technical University of Munich Munich Germany Department of Computer Science University of Haute-Alsace Mulhouse France Hamlyn Centre for Robotic Surgery Imperial College London United Kingdom Department of Advanced Medical Initiatives Graduate School of Medical Sciences Kyushu University Fukuoka Japan Department for General Visceral and Transplant Surgery Heidelberg University Hospital Heidelberg Germany Department of Computer Science Johns Hopkins University BaltimoreMD United States University of Leipzig Leipzig Germany ICube University of Strasbourg CNRS IHU Strasbourg France Department of Surgery University of Wisconsin MadisonWI United States IWR Heidelberg University Heidelberg Germany Department of Computer Science University College London London United Kingdom Université de Rennes 1 Rennes France INSERM Rennes France

Future advances in surgical care require, to a greater and greater extent, a close partnership between caregivers, patients, technology, and information systems. As part of the move towards personalized medicine, interventional care will increasingly transform from an artisanal craft based on physicians’ individual experiences, preferences and traditions into a discipline that relies on objective decision-making based on large-scale data from heterogeneous sources. Copyright © 2017, The Authors. All rights reserved.

关键词： Surgery

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A 3D simulation for social human-robot interaction with ontology-based robot knowledge

A 3D simulation for social human-robot interaction with onto...

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International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Euijun Hwang Sangyun Lee Yoonseob Lim Jongsuk Choi Department of Computer Science and Information System University of Auckland Auckland New Zealand Department of Electrical Engineering Seoul National University of Science and Technology Seoul Korea Center for Robotics Research Korea Institute of Science and Technology Seoul Korea

This paper introduces a preliminary result for social human-robot interaction architecture and its application. System includes human perception module that receives visual data from 3D human simulation and knowledge module that contains various concepts for social interaction situation. The proposed system has been tested for inferring social interaction type based on a simple social interaction scenario.

关键词： Robots

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Layered ensemble model for short-term traffic flow forecasting with outlier detection

Layered ensemble model for short-term traffic flow forecasti...

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IEEE International Forum on Research and Technologies for Society and Industry Leveraging a better tomorrow (RTSI)

作者： Amr Abdullatif Stefano Rovetta Francesco Masulli Department of Computer Science Robotics and Systems Engineering University of Genova Genova Italy College of Science and Technology Temple University Sbarro Institute for Cancer Research and Molecular Medicine Philadelphia PA USA

ISBN: (纸本)9781509011322

Real time traffic flow forecasting is a necessary requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. This paper focuses on short-term traffic flow forecasting by taking into consideration both spatial (road links) and temporal (lag or past traffic flow values) information. We propose a Layered Ensemble Model (LEM) which combines Artificial Neural Networks and Graded Possibilistic Clustering obtaining an accurate forecast of the traffic flow rates with outlier detection. Experimentation has been carried out on two different data sets. The former was obtained from real UK motorway and the later was obtained from simulated traffic flow on a street network in Genoa (Italy). The proposed LEM model for short-term traffic forecasting provides promising results and given the ability for outlier detection, accuracy, robustness of the proposed approach, it can be fruitful integrated in traffic flow management systems.

关键词： Forecasting Predictive models Neural networks Roads Computational modeling Data models Industries

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Design and preliminary characterization of a soft wearable exoskeleton for upper limb

Design and preliminary characterization of a soft wearable e...

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IEEE/RAS-EMBS International Conference on Biomedical robotics and Biomechatronics (BioRob)

作者： Leonardo Cappello Dinh Khanh Binh Shih-Cheng Yen Lorenzo Masia Department of Robotics Brain and Cognitive Science Istituto Italiano di Tecnologia Genova Italy School of Mechanical & Aerospace Engineering Nanyang Technological University Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (纸本)9781509032884

Exoskeletons targeting the upper limb have been broadly developed both for rehabilitation and to augment user's physical performance. Generally, they are rigid robotic interfaces characterized by a non negligible mechanical impedance at the end effector and consequently perceived by the upper limbs as an external body. The rigid frame, moreover, adds kinematic constrains to the natural joint kinematics which may result in discomfort and ultimately in pain. The concept of soft wearable exoskeleton (or exosuit) has been developed and tested for the lower limb and the hand to address such issues thanks to their minimal inertial contribution and influence on the natural kinematics. In the current paper the design of an soft robotic interface for the elbow joint is presented, whose aim is to provide assistance torque to the targeted joint to facilitate the execution of the activities of daily living. Differently from the state-of-the-art design solutions, our system is able to drive both flexion and extension of the same joint with a single motor in an agonist-antagonist fashion, making the actuation stage compact and energy efficient. A clutching mechanism is also included in the design in order to save power during static configuration, preventing the motor to hold the joint position for a large amount of time. An exosuit has been designed to transfer the torque of the actuator to the biomechanical joint by means of Bowden cables. Two series elastic elements are employed to overcome the drawbacks of the agonist-antagonist mechanism and to provide additional compliance at the end effector. A preliminary test has been finally performed in order to characterize the actuation.

关键词： Cable shielding Actuators Springs Gears Brushless DC motors

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