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2010 11th International Workshop on Variable Structure Systems, VSS 2010

作者： Rubagotti, Matteo Estrada, Antonio Castaños, Fernando Ferrara, Antonella Fridman, Leonid Department of Mechanical and Structural Engineering Università degli Studi di Trento Via Mesiano 77 38123 Trento Italy Department of Control and Robotics Engineering Faculty C.P. 04510. Mexico City Mexico McGill Center for Intelligent Machines Montreal QC Canada Department of Computer Engineering and Systems Science Università degli Studi di Pavia Via Ferrata 1 27100 Pavia Italy

ISBN: (纸本)9781424458318

This paper considers the problem of using an integral sliding mode strategy to reduce the disturbance terms acting on nonlinear systems in regular form. It is proved that the definition of a suitable sliding manifold and the generation of sliding modes upon it can guarantee the minimization of the disturbance terms. Simulation examples shows the effectiveness of the proposal. © 2010 IEEE.

关键词： Disturbance rejection

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Analysis of task feasibility for a home robot using prismatic joints

Analysis of task feasibility for a home robot using prismati...

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2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Tomoaki Mashimo Rosen Diankov Takateru Urakubo Takeo Kanade Robotics Institute Carnegie Mellon University Pittsburgh PA USA Department of Computer Science and Systems Engineering Kobe University Kobe Japan

This paper evaluates the dynamic and kinematic properties of a prismatic mechanism and shows its capabilities in performing home manipulation tasks when integrated into a robotic arm. Our design is motivated from the observation that human hand motions often follow a linear trajectory when manipulating everyday objects. We present the mechanical design for a light-weight, energy-efficient robot named PRISM that emphasizes translational motion. By simulating the dynamics equations and comparing the structure of commonly used anthropomorphic arms and our proposed arm, we verify that translational motion is more energy efficient with PRISM, and the robot can maneuver itself in narrower places. Through simulation experiments using state of the art manipulation planning algorithms, we analyze the success rates of PRISM and an anthropomorphic robot arm in performing basic tasks. The simulation experiments center on pick-and-place tasks in cluttered kitchen scenes. We show a real-world prototype of PRISM and perform several manipulation experiments with it.

关键词： Robots Elbow Wrist Integrated circuit modeling Prototypes Torso

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Singularity-based mechanism with high responsiveness

Singularity-based mechanism with high responsiveness

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2010 IEEE/RSJ International Conference on Intelligent Robots and Systems

作者： Tomoaki Mashimo Takateru Urakubo Takeo Kanade Robotics Institute Carnegie Mellon University Pittsburgh PA USA Department of Computer Science and Systems Engineering Kobe University Kobe Japan

We propose a singularity-based mechanism (SBM) to exploit the singular configuration that improves the angular acceleration instead of constraining the movement. The tradeoff between the responsiveness and the range of motion is achieved by varying a length of linkage in the SBM. In this paper, we clarify the responsiveness of the SBM using the dynamics analysis. For the demonstration, we build an experimental SBM system with the high responsiveness, a practical range of motion, and a size comparable to a human arm. In the experiment, the effectiveness of the SBM is shown in a vertical lifting task. The characteristic of the SBM that generates a large acceleration at start is similar to the human arm moved by a muscle. The similarity between the SBM and the human arm is analyzed in terms of the static torque.

关键词： Actuators

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Learning to navigate through crowded environments

Learning to navigate through crowded environments

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IEEE International Conference on robotics and Automation (ICRA)

作者： Peter Henry Christian Vollmer Brian Ferris Dieter Fox Department of Computer Science & Engineering University of Washington Seattle WA USA Neuroinformatics and Cognitive Robotics Laboratory Ilmenau University of Technology Germany

The goal of this research is to enable mobile robots to navigate through crowded environments such as indoor shopping malls, airports, or downtown side walks. The key research question addressed in this paper is how to learn planners that generate human-like motion behavior. Our approach uses inverse reinforcement learning (IRL) to learn human-like navigation behavior based on example paths. Since robots have only limited sensing, we extend existing IRL methods to the case of partially observable environments. We demonstrate the capabilities of our approach using a realistic crowd flow simulator in which we modeled multiple scenarios in crowded environments. We show that our planner learned to guide the robot along the flow of people when the environment is crowded, and along the shortest path if no people are around.

关键词： Navigation Learning Cost function Mobile robots Airports Robot sensing systems Gaussian processes robotics and automation USA Councils computer science

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On Adapting Pixel-based Classification to Unsupervised Texture Segmentation

On Adapting Pixel-based Classification to Unsupervised Textu...

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International Conference on Pattern Recognition

作者： Jaime Melendez Domenec Puig Miguel Angel Garcia Intelligent Robotics and Computer Vision Group Department of Computer Science and Mathematics Rovira i Virgili University Tarragona Spain Department of Informatics Engineering Autonomous University of Madrid Madrid Spain

ISBN: (纸本)9781424475421

An inherent problem of unsupervised texture segmentation is the absence of previous knowledge regarding the texture patterns present in the images to be segmented. A new efficient methodology for unsupervised image segmentation based on texture is proposed. It takes advantage of a supervised pixel-based texture classifier trained with feature vectors associated with a set of texture patterns initially extracted through a clustering algorithm. Therefore, the final segmentation is achieved by classifying each image pixel into one of the patterns obtained after the previous clustering process. Multi-sized evaluation windows following a top-down approach are applied during pixel classification in order to improve accuracy. The proposed technique has been experimentally validated on MeasTex, VisTex and Brodatz compositions, as well as on complex ground and aerial outdoor images. Comparisons with state-of the-art unsupervised texture segmenters are also provided.

关键词： Image segmentation Pixel Clustering algorithms Accuracy Feature extraction Classification algorithms Image edge detection

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Robust Color Image Segmentation through Tensor Voting

Robust Color Image Segmentation through Tensor Voting

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International Conference on Pattern Recognition

作者： Rodrigo Moreno Miguel Angel Garcia Domenec Puig Intelligent Robotics and Computer Vision Group Department of Computer Science and Mathematics Rovira i Virgili University Tarragona Spain Department of Informatics Engineering Autonomous University of Madrid Madrid Spain

ISBN: (纸本)9781424475421

This paper presents a new method for robust color image segmentation based on tensor voting, a robust perceptual grouping technique used to extract salient information from noisy data. First, an adaptation of tensor voting to both image denoising and robust edge detection is applied. Second, pixels in the filtered image are classified into likely-homogeneous and likely-inhomogeneous by means of the edginess maps generated in the first step. Third, the likely-homosgeneous pixels are segmented through an efficient graph-based segmenter. Finally, a modified version of the same graph-based segmenter is applied to the likely-inhomogeneous pixels in order to obtain the final segmentation. Experiments show that the proposed algorithm has a better performance than the state-of-the-art.

关键词： Pixel Image segmentation Tensile stress Robustness Image color analysis Image edge detection Noise measurement

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Computationally effective stereovision SLAM

Computationally effective stereovision SLAM

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IEEE International Workshop on Imaging Systems and Techniques (IST)

作者： Lazaros Nalpantidis Georgios Ch. Sirakoulis Andrea Carbone Antonios Gasteratos Laboratory of Robotics and Automation Department of Production and Management Engineering Democritus University of Thrace Xanthi Greece Laboratory of Electronics Department of Electrical and Computer Engineering Democritus University of Thrace Xanthi Greece Autoagent Laboratory of Cognitive Robotics Department of Computer and Systems Science University of Roma La Sapienza Rome Italy

In this paper a visual Simultaneous Localization and Mapping (SLAM) algorithm suitable for indoor area measurement applications is proposed. The algorithm is focused on computational effectiveness. The only sensor used is a stereo camera placed onboard a moving robot. The algorithm processes the acquired images calculating the depth of the scenery, detecting occupied areas and progressively building a map of the environment. The stereo vision-based SLAM algorithm embodies a custom-tailored stereo correspondence algorithm, the robust scale and rotation invariant feature detection and matching Speeded Up Robust Features (SURF) method, a computationally effective v-disparity image calculation scheme, a novel map-merging module, as well as a sophisticated Cellular Automata (CA)-based enhancement stage. The proposed algorithm is suitable for autonomously mapping and measuring indoor areas using robots. The algorithm is presented and experimental results for self-captured image sets are provided and analyzed.

关键词： Simultaneous localization and mapping Area measurement Robustness computer vision Robot vision systems Cameras Robot sensing systems robotics and automation Image analysis Algorithm design and analysis

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Editorial Special issue on approximate dynamic programming and reinforcement learning

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控制理论与应用（英文版） 2011年第3期 309-309页

作者： Silvia Ferrari Jagannathan Sarangapani Frank L. Lewis Laboratory for Intelligent Systems and Control(LISC)Department of Mechanical Engineering & Materials Science Box 90300 Duke University Durham NC 27708-0005 Department of Electrical & Computer Engineering University of Missouri-Rolla MO 65401 U.S.A. Automation and Robotics Research Institute The University of Texas at Arlington 7300 Jack Newell Blvd. S Ft. Worth Texas 76118-7115 U.S.A.

We are extremely pleased to present this special issue of the Journal of Control Theory and *** dynamic programming (ADP) is a general and effective approach for solving optimal control and estimation problems by adapting to uncertain environments over *** optimizes the sensing objectives accrued over a future time interval with respect to an adaptive control law,conditioned on prior knowledge of the system,its state,and uncertainties.A numerical search over the present value of the control minimizes a Hamilton-Jacobi-Bellman (HJB) equation providing a basis for real-time,approximate optimal control.

关键词： reinforcement learning dynamic programming optimal control effective approach prior knowledge Control Theory real-time control law problems special search future ADP basis

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On challenges of robot assisted radiotherapy for lung tumors

On challenges of robot assisted radiotherapy for lung tumors

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IEEE International Conference on robotics and Biomimetics

作者： Lei Ma Christian Herrmann Klaus Schilling School of Electrical Engineering Southwest Jiaotong University Chengdu China Department of Computer Science VII: Robotics and Telematics University of Würzburg Wurzburg Germany

This paper is concerned with recent development in robot assisted radiotherapy for lung tumors. The paper first analyzes technical challenges regarding tumor position determination and prediction, by invasive and non-invasive methods, correlation models of the tumor motion and the respiratory signals, as well as modeling and control of the robot manipulator. Several currently available solutions and concepts are then briefly introduced. Emphasis is placed on the ATTS (adaptive tumor tracking system) system developed at the University of Würzburg. Within the ATTS, information of the tumor motion is used to control a robotic treatment couch HexaPOD, which moves in six degrees of freedom and maintains the tumor in a certain fixed spatial position. With this new technology it is possible to avoid gating during the radiotherapy as well as active breathing control, such that duration and cost of the therapy as well as trauma of the patient can be reduced. The tumor position is obtained by data fusion from two sensing system. Correlation methods for data fusion were extensively investigated and a prediction model for tumor motion is found that can forecast the tumor position for up to one respiratory period. Modeling of the HexaPOD treatment couch is addressed. The most suitable model is found to be a low-order linear dynamic equation together with a saturation component. Three different control methods and comparative test results are then presented to show feasibility of the proposed model and control schemes.

关键词： Tumors Robots Adaptation model Predictive models Tracking Cameras Data models

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Reducing stick-slip motion in one-dimensional nano manipulation by real-time feedback control

Reducing stick-slip motion in one-dimensional nano manipulat...

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2010 10th IEEE Conference on Nanotechnology, NANO 2010

作者： Zhang, Jing Miao, Lei Wu, Re-Bing Xi, Ning Li, Chun-Wen Wang, Yue-Chao Tarn, Tzyh-Jong Department of Automation Tsinghua University Beijing 100084 China Center for Quantum Information Science and Technology Tsinghua National Laboratory for Information Science and Technology Beijing 100084 China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Beijing 110016 China Department of Electrical and Computer Engineering Michigan State University East Lansing MI 48824 United States Department of Electrical and Systems Engineering Washington University St. Louis MO 63130 United States

ISBN: (纸本)9781424470334

When a micro cantilever with a nanoscale tip is manipulated on a substrate with atomic roughness, e.g., pushing an atomic-scale sample or etching the surface of the substrate to draw desired patterns, the periodical lateral frictional forces with stochastic fluctuations will induce stick-slip motion of the cantilever tip, which may greatly influence the precision of the nano manipulation. To reduce such a stick-slip motion, we propose a feedback control strategy based on the position estimation of the cantilever tip to compensate the periodical frictional force. Numerical simulations show that the motion of the cantilever tip under feedback control can track the desired trajectory asymptotically. Our proposal can aL be extended to the case when the cantilever tip moves over a Gaussian-shape defection on the substrate and when the stochastic fluctuations in the lateral force are with non-zero correlation time. ©2010 IEEE.

关键词： Feedback control

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