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An intelligent mobile robot navigation technique using RFID technology

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT 2008年第9期57卷 1908-1917页

作者： Gueaieb, Wail Miah, Md. Suruz Univ Ottawa Sch Informat Technol & Engn MIRaM Lab Ottawa ON K1N 6N5 Canada

This paper presents an innovative mobile robot navigation technique using Radio Frequency IDentification (RFID) technology. Navigation based on processing some analog features of an RFID signal is a promising alternative to different types of navigation methods in the state of the art. The main idea is to exploit the ability of a mobile robot to navigate a priori unknown environments without a vision system and without building an approximate map of the robot workspace, as is the case in most other navigation algorithms. This paper discusses how this is achieved by placing RFID tags in the 3-D space so that the lines linking their projections on the ground define the "free ways" along which the robot can (or is desired to) move. The suggested algorithm is capable of reaching a target point in its a priori unknown workspace, as well as tracking a desired trajectory with a high precision. The proposed solution offers a modular, computationally efficient, and cost-effective alternative to other navigation techniques for a large number of mobile robot applications, particularly for service robots, such as, for instance, in large offices and assembly lines. The effectiveness of the proposed approach is illustrated through a number of computer simulations considering testbeds of various complexities.

关键词： fuzzy logic mobile robots navigation position control Radio Frequency IDentification (RFID) robot sensing systems

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Proceedings of SPIE - intelligent robots and computer vision XXV: algorithms, techniques, and Active vision

Proceedings of SPIE - Intelligent Robots and Computer Vision...

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intelligent robots and computer vision XXV: algorithms, techniques, and Active vision

ISBN: (纸本)9780819469243

The proceedings contain 33 papers. The topics discussed include: new design method for a hierarchical SVM-based classifier;eclectic theory of intelligent robots;emerging directions in lunar and planetary robotics;robust pedestrian detection and tracking in crowded scenes;multiple pedestrian detection using IR LED stereo camera;a fixed-point kanade lucas tomasi tracker implementation for smart cameras;detection and tracking using multi-color target models;a real time vehicle tracking system for an outdoor mobile robot;an occlusion robust likelihood integration method for multi-camera people head tracking;articulated motion analysis via axis-based representation;an automatic quality system for injection molding;a concept for ubiquitous robotics in industrial environment;and dynamic template size control in digital image correlation based strain measurements.

关键词： computer vision

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Fast Autofocus of Microscopy Images Based on Depth-from-Defocus

Fast Autofocus of Microscopy Images Based on Depth-from-Defo...

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2008 IEEE/RSJ International Conference on intelligent robots and Systems, Pages 2611-3132

作者： Liguo Chen Zhiliang Yang Lining Sun Robotics Institute of Harbin Institute of Technology Harbin China

ISBN: (纸本)9781424420575

Microscopic computer vision differs significantly from macroscale computer vision. Autofocusing techniques is of fundamental importance to automated micromanipulation in providing high level task understanding, task planning and real time control. Depth-from-Focus (DFF) based autofocusing method is widely used in many microscope systems, while the low efficiency limited its application in micromanipulation system which needs fast autofocus for real time control. In this paper, Depth-From-Defocus (DFD) algorithms are proposed to improve autofocusing performance and robustness for microscopic optics. Two different schemes based on look-up table and function relation are investigated and evaluated through actual experiments. Experimental results validate the performances of the two proposed autofocusing methods.

关键词： Real time control images auto-focus defocusing computer vision Micromanipulation Fasting Microscopy

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A real time vehicles tracking system for an outdoor mobile robot

A real time vehicles tracking system for an outdoor mobile r...

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Conference on intelligent robots and computer vision XXV - algorithms, techniques, and Active vision

作者： Ge, Kanbing Forging Ctr Co Ltd Osaka Japan

This paper describes progress toward a street-crossing system for an outdoor mobile robot. The system can detect and track vehicles in real time. It reasons about extracted motion regions to decide when it is safe to ... 详细信息

ISBN: (纸本)9780819469243

关键词： mobile robots street crossing computer vision vehicle tracking

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Single-camera stereo vision for obstacle detection in mobile robots

Single-camera stereo vision for obstacle detection in mobile...

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Conference on intelligent robots and computer vision XXV - algorithms, techniques, and Active vision

作者： Lovegrove, William Brame, Ben Bob Jones Univ Greenville SC 29607 USA

ISBN: (纸本)9780819469243

Stereo vision is attractive for autonomous mobile robot navigation, but the cost and complexity of stereo camera systems and the computational requirements make full stereo vision impractical. A novel optical system allows the capture of a pair of short, wide stereo images from a single camera, which are then processed to detect vertical edges and infer obstacle positions and locations within the planar field of view, providing real-time obstacle detection. Our optical system involves a pair of right-angle prisms stacked vertically, splitting the camera field of view vertically in half. Right angle mirrors on either side redirect the image forward but at a horizontally displaced location, creating two virtual cameras. Tilting these mirrors provides an overlapping image area. Alternately, tilting the prisms produces the same effect. This image area is wide but not very tall. However, in a mobile robot scenario the majority of obstacles of interest intersect this field of view.

关键词： stereo single camera mobile robots obstacle detection computer vision

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The 15^th Annual intelligent Ground Vehicle Competition:: intelligent ground robots created by intelligent students

The 15<SUP>th</SUP> Annual Intelligent Ground Vehicle Compet...

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Conference on intelligent robots and computer vision XXV - algorithms, techniques, and Active vision

作者： Theisen, Bernard L. USA Tank Automotive Res Ctr Dev & Engn Warren MI 48397 USA

ISBN: (纸本)9780819469243

The intelligent Ground Vehicle Competition (IGVC) is one of three, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI) in the 1990s. The IGVC is a multidisciplinary exercise in product realization that challenges college engineering student teams to integrate advanced control theory, machine vision, vehicular electronics, and mobile platform fundamentals to design and build an unmanned system. Teams from around the world focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 15 years, the competition has challenged undergraduate, graduate and Ph.D. students with real world applications in intelligent transportation systems, the military and manufacturing automation. To date, teams from over 50 universities and colleges have participated. This paper describes some of the applications of the technologies required by this competition and discusses the educational benefits. The primary goal of the IGVC is to advance engineering education in intelligent vehicles and related technologies. The employment and professional networking opportunities created for students and industrial sponsors through a series of technical events over the four-day competition are highlighted. Finally, an assessment of the competition based on participation is presented.

关键词： intelligent robots autonomous systems ground vehicles engineering education IGVC

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Virtual force field based obstacle avoidance and agent based intelligent mobile robot

Virtual force field based obstacle avoidance and agent based...

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Conference on intelligent robots and computer vision XXV - algorithms, techniques, and Active vision

作者： Sarkar, Saurabh Reynolds, Scott Hall, Ernest Univ Cincinnati Dept Mech Engn 2600 Clifton Ave Cincinnati OH 45221 USA Univ Cincinnati Dept Comp Sci Cincinnati OH 45221 USA

ISBN: (纸本)9780819469243

This paper presents a modified virtual force based obstacle avoidance approach suited for laser range finder. The modified method takes advantage of the polar coordinate based data sent by the laser sensor by mapping the environment in a polar coordinate system. The method also utilizes a Gaussian function based certainty values to detect obstacle. The method successfully navigates through complex obstacles and reaches target GPS waypoints.

关键词： virtual force field laser ranger finder agents

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Fruit shape classification using support vector machine

Fruit shape classification using support vector machine

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Conference on intelligent robots and computer vision XXV - algorithms, techniques, and Active vision

作者： Gui, Jiangsheng Rao, Xiuqin Ying, Yibin Zhejiang Sci Tech Univ Dept Elect & Informat Hangzhou 310018 Peoples R China Zhejiang Univ Dept Biosyst Engn & Food Sci Hangzhou 310029 Peoples R China

ISBN: (纸本)9780819469243

A new method along with shape descriptor using support vector machine for classify fruit shape is developed, the image is first subjected to a normalization process using its regular moments to obtain scale and translation invariance, the rotation invariant Zernike features are then extracted from the scale and translation normalized images and the numbers of features are decided by primary component analysis (PCA), at last. these features are input to support vector machine (SVM) classifier and are compared to different classifiers. This method using support vector machine as classifier performs better than traditional approaches that is verified by some experiments.

关键词： machine vision shape classification fruit sorting SVM

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Creative learning for intelligent robots

Creative learning for intelligent robots

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Conference on intelligent robots and computer vision XXV - algorithms, techniques, and Active vision

作者： Liao, Xiaoqun Hall, Ernest L. Univ Cincinnati Ctr Robot Res Cincinnati OH 45221 USA

ISBN: (纸本)9780819469243

This paper describes a methodology for creative learning that applies to man and machines. Creative learning is a general approach used to solve optimal control problems. The creative controller for intelligent machines integrates a dynamic database and a task control center into the adaptive critic learning model. The task control center can function as a command center to decompose tasks into sub-tasks with different dynamic models and criteria functions, while the dynamic database can act as an information system. To illustrate the theory of creative control, several experimental simulations for robot arm manipulators and mobile wheeled vehicles were included. The simulation results showed that the best performance was obtained by using adaptive critic controller among all other controllers. By changing the paths of the robot arm manipulator in the simulation, it was demonstrated that the learning component of the creative controller was adapted to a new set of criteria. The Bearcat Cub robot was another experimental example used for testing the creative control learning. The significance of this research is to generalize the adaptive control theory in a direction toward highest level of human learning - imagination. In doing this it is hoped to better understand the adaptive learning theory and move forward to develop more human-intelligence-like components and capabilities into the intelligent robot. It is also hoped that a greater understanding of machine learning will motivate similar studies to improve human learning.

关键词： adaptive critic design dynamic programming creative learning Neurocontrol intelligent robots artificial intelligence

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Searching strain field parameters by genetic algorithms

Searching strain field parameters by genetic algorithms

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Conference on intelligent robots and computer vision XXV - algorithms, techniques, and Active vision

作者： Koljonen, Janne Mantere, Timo Kanniainen, Olli Alander, Jarmo T. Univ Vaasa Dept Elect Engn & Automat FIN-65101 Vaasa Finland

ISBN: (纸本)9780819469243

This paper studies the applicability of genetic algorithms and imaging to measure deformations. Genetic algorithms are used to search for the strain field parameters of images from a uniaxial tensile test. The non-deformed image is artificially deformed according to the estimated strain field parameters, and the resulting image is compared with the true deformed image. The mean difference of intensities is used as a fitness function. Results are compared with a node-based strain measurement algorithm developed by Koljonen et al. The reference method slightly outperforms the genetic algorithm as for mean difference of intensities. The root-mean-square difference of the displacement fields is less than one pixel. However, with some improvements suggested in this paper the genetic algorithm based method may be worth considering, also in other similar applications: Surface matching instead of individual landmarks can be used in camera calibration and image registration. Search of deformation parameters by genetic algorithms could be applied in pattern recognition tasks e.g. in robotics, object tracking and remote sensing if the objects are subject to deformation. In addition, other transformation parameters could be simultaneously looked for.

关键词： deformation genetic algorithms machine vision search tensile testing

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