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International Conference on Advanced robotics (ICAR)

作者： P. Drews L.J. Manso S.C. da Silva Filho P. Núñez Robotics and Artificial Vision Laboratory (RoboLab) University of Extremadura Intelligent Robotics and Automation Group (NAUTEC) Computational Sciences Center Universidade Federal do Rio Grande Brazil

The interest in change detection techniques for autonomous robots has increased considerably during recent years. This is partly due to the fact that changes in robot's working environments are relevant for most tasks and robotics applications. Changes or Novelties are usually detected by comparing the current data acquired by the robot with its previous knowledge (a map or any other model of its surroundings). Gaussian Mixture Models (GMM) have been satisfactorily used for detecting changes in 3D point clouds. However, these methods have drawbacks such as a long computational times and strong dependence on the parameters of the algorithms. In structured environments like offices or homes, it is possible to reduce the number of points to be processed by filtering unlikely-to-change regions of the scene. This paper introduces the concept of Vertical Surface Normal Histogram (VSNH). VSNH provides a method for removing from the point clouds acquired those points associated to the main planes: ceiling, walls and floor. Removing these points decreases the size of the problem and improves the segmentation of the environment into Gaussian Mixture Models. The experimental results demonstrate that the proposed method based on GMM and VSNH achieves change detection in structured indoor environments faster and more accurately than previous approaches.

关键词： Vectors Histograms Robots Three-dimensional displays Measurement Change detection algorithms Gaussian mixture model

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Development of robust behaviour recognition for an at-home biomonitoring robot with assistance of subject localization and enhanced visual tracking

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Scientific World Journal 2014年第1期2014卷 280207-280207页

作者： Imamoglu, Nevrez Dorronzoro, Enrique Wei, Zhixuan Shi, Huangjun Sekine, Masashi González, José Gu, Dongyun Chen, Weidong Yu, Wenwei Graduate School of Engineering Chiba University Chiba 263-8522 Japan Research Center for Frontier Medical Engineering Chiba University Chiba 263-8522 Japan Department of Electronic Technology University of Seville Seville 41012 Spain Institute of Robotics and Intelligent Information Processing Department of Automation Shanghai Jiao Tong University Shanghai 200240 China Department of Biomedical Engineering Shanghai Jiao Tong University Shanghai 200030 China Spanish National Research Council Bioengineering Group Madrid 28500 Spain

Our research is focused on the development of an at-home health care biomonitoring mobile robot for the people in demand. Main task of the robot is to detect and track a designated subject while recognizing his/her activity for analysis and to provide warning in an emergency. In order to push forward the system towards its real application, in this study, we tested the robustness of the robot system with several major environment changes, control parameter changes, and subject variation. First, an improved color tracker was analyzed to find out the limitations and constraints of the robot visual tracking considering the suitable illumination values and tracking distance intervals. Then, regarding subject safety and continuous robot based subject tracking, various control parameters were tested on different layouts in a room. Finally, the main objective of the system is to find out walking activities for different patterns for further analysis. Therefore, we proposed a fast, simple, and person specific new activity recognition model by making full use of localization information, which is robust to partial occlusion. The proposed activity recognition algorithm was tested on different walking patterns with different subjects, and the results showed high recognition accuracy. © 2014 Nevrez Imamoglu et al.

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A Systematic Approach to intelligent Maintenance of Production Systems with a Framework for Embedded Implementation

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IFAC Proceedings Volumes 2013年第7期46卷 23-28页

作者： Edzel R. Lapira Behrad Bagheri Wenyu Zhao Jay Lee Renato VB Henriques Carlos E. Pereira LB Piccoli CSS Guimarães NSF I/UCRC for Intelligent Maintenance Systems University of Cincinnati Cincinnati OH 45221 USA UFRGS - Control Automation and Robotics Group - Av. Osvaldo Aranha 103 Bom Fim. CEP:90031-190 Porto Alegre RS Brazil

To achieve worry-free production and prevent unexpected downtime, predictive maintenance has become a prevailing strategy, supported by prognostics and health management techniques. In this paper, a systematic data-driven approach for intelligent maintenance is discussed, as well as an embedded system architecture for fault detection and prediction. Two case studies are presented, including performance prediction for wire-twisting machine based on temperature data, and an embedded solution for electric valve actuator monitoring.

关键词： intelligent Maintenance Predictive Maintenance Embedded Intelligence

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Fast and adaptive 3D change detection algorithm for autonomous robots based on Gaussian Mixture Models

Fast and adaptive 3D change detection algorithm for autonomo...

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IEEE International Conference on robotics and automation (ICRA)

作者： P. Drews S. C. da Silva Filho L. F. Marcolino P. Núñez Intelligent Robotics and Automation Group (NAUTEC) Computational Sciences Center Universidade Federal do Rio Grande Rio Grande do Sul Brazil RoboLaboratoryGroup Department Tecnologfa de los Computadores y las Comunicaciones Universidad de Extremadura Spain

Nowadays, the advance of the technology allows robots to acquire dense point clouds decreasing the price and increasing the performance. However, it is a hard task to deal with due to the large amount of points, the redundancy and the noise. This paper proposes an adaptable system to build a 3D feature model of point clouds using Gaussian Mixture Models. These 3D models are used in order to detect changes in the autonomous robot's working environment. The presented work describes an efficient change detection system based on two consecutive stages. First, a top-down approach estimates features using Gaussian Mixture Models. The presented new approach improves the performance of previous related works in terms of computational load and robustness, nevertheless the system is selection criteria dependent. Thus, the efficiency of different selection criteria are evaluated and compared in this paper. Experimental results demonstrate that the Minimum Distance Length (MDL) criteria outperforms the other studied methods. In the second stage, a change detection method is performed using the previously estimate Mixture of Gaussians. The proposed full system is able to detect changes using Gaussian Mixture Models with a reduced computational cost in relation to state-of-art algorithms.

关键词： Computational modeling Robots Solid modeling Noise Three-dimensional displays Navigation Software

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Automating and accelerating the additive manufacturing design process with multi-objective constrained evolutionary optimization and HPC/cloud computing

Automating and accelerating the additive manufacturing desig...

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2012 Future of Instrumentation International Workshop, FIIW 2012

作者： Buckner, Mark A. Love, Lonnie J. RF Communications and Intelligent Systems Group Oak Ridge National Laboratory Oak Ridge TN United States Automation Robotics and Manufacturing Group Oak Ridge National Laboratory Oak Ridge TN United States

ISBN: (纸本)9781467324823

The ultimate objective of additive manufacturing is the implementation of techniques that can be used throughout the full manufacturing cycle. However, since its introduction, the additive manufacturing process has been used for little more than pre-production prototyping. The goal of some current work at ORNL is to change that reality. ORNL recently completed the first step towards optimizing the final design and manufacture of a component part (a cantilever in this case) using computer-aided design (CAD) tools, finite element analysis and simulations, and internally-developed optimization software. This paper will describe the present design process, the tools used, and the progress made thus far. It will also discuss the recent porting of ORNL's Multi-Objective Constrained Evolutionary Optimization (MOCEO) algorithms to ORNL's high performance computing (HPC) resources and to other resources available for Cloud computing, and the path forward for implementing additive manufacturing designs on these resources. © 2012 IEEE.

关键词： Computer aided design

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Automating and accelerating the additive manufacturing design process with multi-objective constrained evolutionary optimization and HPC/Cloud computing

Automating and accelerating the additive manufacturing desig...

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Future of Instrumentation International Workshop (FIIW)

作者： Mark A. Buckner Lonnie J. Love RF Communications & Intelligent Systems Group Automation Robotics and Manufacturing Group Oak Ridge National Laboratory Oak Ridge TN USA

关键词： Manufacturing Additives Solid modeling Optimization Computational modeling Design automation Sociology

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Human actions recognition using Fuzzy PCA and discriminative hidden model

Human actions recognition using Fuzzy PCA and discriminative...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Xiaofei Ji Honghai Liu Yibo Li Intelligent Systems and Biomedical Robotics Group School of Creative Technologies University of Portsmouth Portsmouth UK School of Automation Shenyang Institute of Aeronautical Engineering Shenyang China

As a temporal classification problem, visual-based human actions recognition is an important component for some potential applications. In this paper, we combine Fuzzy Principle Component Analysis(Fuzzy PCA) and hidden Conditional Random Fields(HCRFs) to achieve a viewpoint insensitive human action recognition. Fuzzy PCA is used to reduce the dimension of the silhouette image features to obtain the compact representation of action space. HCRFs is applied to model the human actions from different actors and different viewpoints. This method can relax the independence assumption of the generative model. Experiment results on a public dataset demonstrate the effectiveness and robustness of our method.

关键词： Humans Hidden Markov models Principal component analysis Cameras Training Eigenvalues and eigenfunctions Feature extraction

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Pedestrian detection using color symmetry phases

Pedestrian detection using color symmetry phases

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International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology, ECTI-CON

作者： J. Janta P. Kumsawat K. Attakitmongcol A. Srikaew Robotics Automation Research Unit for Real-World Applications Intelligent System Group School of Electrical Engineering Suranaree University슠of Technology Nakhon Ratchasima Thailand

Pedestrian detection is one of the most important research contents of road safety. The crucial idea behind such pedestrian safety systems is to protect the driver and pedestrian from any accident. In this paper, a pedestrian feature extraction based on color symmetry phases is presented. By examining symmetry phases in multiple color spaces, the segmentation results are significantly improved which allows support vector machines to be able to efficiently classify and recognize the pedestrian. The proposed system is capable of detecting multiple pedestrians from complex background and providing size and position information of pedestrians within the image. Pedestrians with different sizes, shapes, postures, and clothes can be detected effectively. Results and discussions are presented.

关键词： Image color analysis Feature extraction Shape Pixel Manganese Motion segmentation Image segmentation

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Supervising Remote Humanoids Across Intermediate Time Delay

Supervising Remote Humanoids Across Intermediate Time Delay

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IEEE-RAS International Conference on Humanoid Robots

作者： Kimberly Hambuchen William Bluethmann Michael Goza Robert Ambrose Kenneth Rabe Mark Allan Automation Robotics and Simulation Division NASA-Johnson Space Center Houston TX USA Planning Software Systems Group Jet Propulsion Laboratory/California Institute of Technology Pasadena CA USA Intelligent Robotics Group NASA Ames Research Center Moffett Field CA USA

ISBN: (纸本)1424401992;142440200X

The President's Vision for Space Exploration, laid out in 2004, relies heavily upon robotic exploration of the lunar surface in early phases of the program. Prior to the arrival of astronauts on the lunar surface, these robots will be required to be controlled across space and time, posing a considerable challenge for traditional telepresence techniques. Because time delays will be measured in seconds, not minutes as is the case for Mars Exploration, uploading the plan for a day seems excessive. An approach for controlling humanoids under intermediate time delay is presented. This approach uses software running within a ground control cockpit to predict an immersed robot supervisor's motions which the remote humanoid autonomously executes. Initial results are presented

关键词： Delay effects Orbital robotics Moon Space exploration Robot vision systems Extraterrestrial measurements Time measurement Mars Motion control Humanoid robots

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Towards Open Architectures for Mobile Robots: ZeeRO

Towards Open Architectures for Mobile Robots: ZeeRO

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IEEE International Conference on automation, Quality and Testing, robotics, AQTR

作者： Radu Bogdan Rusu Radu Robotin Gheorghe Lazea Cosmin Marcu Robotics Research Group Department of Automation Technical University of Cluj Napoca Cluj-Napoca Romania Intelligent Autonomous Systems Computer Science Department Technische Universität München Munich Germany

We report on ongoing research regarding the development of open mobile robot architectures. Preliminary results of our work show that a great degree of modularity and complexity in mobile robot design can be achieved, by simply using off-the-shelf available hardware components. A hardware robotic platform would not be nearly as efficient, if it wouldn't be sustained by an adequate software system. We are proposing the use and the development of the player/stage software project, of which we are active contributors, as the backbone of our software robotic platform. This paper presents the experimental results regarding the development of the ZeeRO mobile robot, with an emphasis on its hardware and software architecture. We give insight on the structure of the main modules (navigation, sensing, processing), as well as the robot's interface with the Player server. Several tests with virtual environment navigation algorithms by means of simulation tools (Stage, Gazebo) have also been conducted. A small section of the paper is dedicated to Javaclient, a player/stage client for the Java programming language, initially developed at the University of Southern California, and later moved to SourceForge

关键词： Mobile robots Hardware Robot sensing systems Navigation Java Computer architecture Software systems Spine Software architecture Testing

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