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检索条件"任意字段=Conference on Intelligent Robots and Computer Vision XXXII - Algorithms and Techniques"

共 372 条记录，以下是121-130 订阅

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A modular real-time vision module for humanoid robots

A modular real-time vision module for humanoid robots

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conference on intelligent robots and computer vision XXIX - algorithms and techniques

作者： Trifan, Alina Neves, Antonio J. R. Lau, Nuno Cunha, Bernardo Univ Aveiro IEETA DETI P-3810193 Aveiro Portugal

ISBN: (纸本)9780819489487

Robotic vision is nowadays one of the most challenging branches of robotics. In the case of a humanoid robot, a robust vision system has to provide an accurate representation of the surrounding world and to cope with all the constraints imposed by the hardware architecture and the locomotion of the robot. Usually humanoid robots have low computational capabilities that limit the complexity of the developed algorithms. Moreover, their vision system should perform in real time, therefore a compromise between complexity and processing times has to be found. This paper presents a reliable implementation of a modular vision system for a humanoid robot to be used in color-coded environments. From image acquisition, to camera calibration and object detection, the system that we propose integrates all the functionalities needed for a humanoid robot to accurately perform given tasks in color-coded environments. The main contributions of this paper are the implementation details that allow the use of the vision system in real-time, even with low processing capabilities, the innovative self-calibration algorithm for the most important parameters of the camera and its modularity that allows its use with different robotic platforms. Experimental results have been obtained with a NAO robot produced by Aldebaran, which is currently the robotic platform used in the RoboCup Standard Platform League, as well as with a humanoid build using the Bioloid Expert Kit from Robotis. As practical examples, our vision system can be efficiently used in real time for the detection of the objects of interest for a soccer playing robot (ball, field lines and goals) as well as for navigating through a maze with the help of color-coded clues. In the worst case scenario, all the objects of interest in a soccer game, using a NAO robot, with a single core 500Mhz processor, are detected in less than 30ms. Our vision system also includes an algorithm for self-calibration of the camera parameters as well

关键词： Robotics robotic soccer computer vision object recognition humanoid robots color classification

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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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Research and Development of Ro-Boat - An Autonomous River Cleaning Robot

Research and Development of Ro-Boat - An Autonomous River Cl...

引用

conference on intelligent robots and computer vision XXXI - algorithms and techniques

作者： Sinha, Aakash Bhardwaj, Prashant Vaibhav, Bipul Mohammad, Noor Omnipresent Robot Technologies Pvt. Ltd. (India) Manav Rachna College Of Engineering (India) Indian Institute Of Technology Guwahati (India) National Institute Of Technology Warangal (India)

ISBN: (纸本)9780819499424

Ro-Boat is an autonomous river cleaning intelligent robot incorporating mechanical design and computer vision algorithm to achieve autonomous river cleaning and provide a sustainable environment. Ro-boat is designed in a modular fashion with design details such as mechanical structural design, hydrodynamic design and vibrational analysis. It is incorporated with a stable mechanical system with air and water propulsion, robotic arms and solar energy source and it is proceed to become autonomous by using computer vision. Both "HSV Color Space" and "SURF" are proposed to use for measurements in Kalman Filter resulting in extremely robust pollutant tracking. The system has been tested with successful results in the Yamuna River in New Delhi. We foresee that a system of Ro-boats working autonomously 24x7 can clean a major river in a city on about six months time, which is unmatched by alternative methods of river cleaning.

关键词： Autonomous robot River cleaning computer vision Multiple object tracking HSV color space SURF Kalman filter

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Navigation using self-initialising active contours.

Navigation using self-initialising active contours.

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conference on intelligent robots and computer vision XVI - algorithms, techniques, Active vision, and Materials Handling

作者： Molloy, D Whelan, PF Vision Systems Laboratory School of Electronic Engineering Dublin City University Glasnevin Dublin 9 Ireland

ISBN: (纸本)0819426407

This paper examines a novel approach for extracting motion information to allow the autonomous navigation of an intelligent mobile robot using computer vision in a moving camera, moving object environment. The approach begins by extracting low-level scene feature information using algorithms such as the SUSAN corner and edge detector. A routine is described for converting the information obtained from these stable features to initialisation information for creating active contour models or 'snakes'. Multiple open and closed active contours are identified in an initialisation frame from this primary feature extraction. These contours are allowed to converge more closely to the features to which they are attached. These contours are then allowed to converge to the features within each frame through image sequences, with criteria for the re-initialisation of new contours when motion information in the sequence or a region becomes sparse. The information received from these contour models is then used to determine. the motion information in the scene. Reasons for this approach are outlined and justified. This theoretical approach is then applied to the practical cases of a mobile robot navigating indoor scenes. Large sections of this approach have been implemented in the Khoros environment, with new routines written for this approach. Promising results are already available and this approach is being examined to allow the extraction of depth information in the scene for assisting navigation using a form of '3-D snakes'.

关键词： corners SUSAN active contours snakes edge-linking

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The 12^TH annual intelligent ground vehicle competition:: Team approaches to intelligent vehicles

The 12<SUP>TH</SUP> annual intelligent ground vehicle compet...

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conference on intelligent robots and computer vision XXII - algorithms, techniques and Active vision

作者： Theisen, BL Maslach, D USA Tank Automat Res Dev & Engn Ctr Warren MI 48397 USA

ISBN: (纸本)081945561X

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. Both U.S. and international teams focus on developing a suite of dual-use technologies to equip ground vehicles of the future with intelligent driving capabilities. Over the past 12 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 43 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 three-day competition are highlighted. Finally, an assessment of the competition based on participant feedback is presented.

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

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Learning from biotechnology;milestones in the prenatal engineering of an intelligent optical sensor: the human eye.

Learning from biotechnology;milestones in the prenatal engin...

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Lauinger, N CORRSYS-DATRON Sensorsysteme GmbH (Germany)

ISBN: (纸本)081944300X

The analysis of the prenatal engineering of the human brain and more specifically that of the human eye may encourage new interpretations and better understanding of 'cortical' processors and lead to better ideas about how to built optical sensors. What human vision at its first processing stages realizes is an adaptive transformation of physical parameters from an 'outer' 4D-spatiotemporal into an 'inner' psychological world or its reciprocal projection and construction of an illusionary (inner or outer) world. The description of some of the most remarkable steps in the development of the human eye before birth, very critical for the optical functionalities in vision, will illustrate the new interpretations.

关键词： Eye Retina Diffraction Brain Diffraction gratings Cones Crystals Rods Sensors Biotechnology

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On the integration of point feature acquisition, tracking and uncalibrated metric reconstruction

On the integration of point feature acquisition, tracking an...

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conference on intelligent robots and computer vision XVIII - algorithms, techniques, and Active vision

作者： Tonko, M Kinoshita, K ATR Human Informat Proc Res Labs Kyoto 6190288 Japan

ISBN: (纸本)0819434302

In this paper a sequence of algorithms for image feature point detection and tracking as well as Euclidian reconstruction of rigid three-dimensional objects from point correspondences is presented. For fully automatic point feature detection, grayvalue images are processed. High-curvature points on contours, i.e. contour elements with locally maximal curvature, are tracked using a normalized correlation algorithm. High-curvature points that could be tracked in a sequence of more than three images are used as point features that are eligible for reconstruction. Since the general way to obtain the epipolar, projective, and Euclidian geometries from point feature correspondences is already solved, here the emphasis is on the performance of the algorithms in the presense of noise. Kanatani's epipolar geometry estimation method is improved and this is experimentally validated. Regarding Bougnoux's Euclidian geometry estimation method, the initial linear solution is now obtained with less uncertainty and the non-linear minimization does no longer converge to a hidden solution. Experimental results are given to assess the system performance.

关键词： 3D scanning Euclidian reconstruction uncalibrated vision real-time feature detection tracking

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Adaptation of human routines to support a robot's tasks planning and scheduling

Adaptation of human routines to support a robot's tasks plan...

引用

conference on intelligent robots and computer vision XXXI - algorithms and techniques

作者： Tikanmaki, A. Feliu, Troyano S. Roning, J. Univ Oulu CSE Dept Oulu Finland

ISBN: (纸本)9780819499424

Service robots usually share their workspace with people. Typically, a robot's tasks require knowing when and where people are, to be able to schedule requested tasks. Therefore, there exists the need to take into account the presence of humans when planning their actions and it is indispensable to have knowledge of robots' environments. It means in practice knowing when (time and events duration) and where (in workspace) a robot's tasks can be performed. This research paper takes steps towards obtaining of the spatial information required to execute software to plan tasks to be performed by a robot. With this aim, a program capable to define meaningful areas or zones in the robot workspace by the use of a clustering is created tied with statistically reasoned time slots when to perform each task. The software is tested using real data obtained from different cameras located along the corridors of CSE Department of University of Oulu.

关键词： service robots learning clustering

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ESTABLISHING IDENTITY AND POSE OF OBJECTS FROM A LIBRARY USING RECIPROCAL BASIS-SET AND DIRECTION-OF-ARRIVAL techniques 12

ESTABLISHING IDENTITY AND POSE OF OBJECTS FROM A LIBRARY USI...

引用

12th conference on intelligent robots and computer vision: algorithms and techniques

作者： WRIGHT, CR VAZ, RF CYGANSKI, D WORCESTER POLYTECH INST DEPT ELECT & COMP ENGNMACHINE VIS LABWORCESTERMA 01609

ISBN: (纸本)0819413208

In many object recognition problems, the object to be identified is one of a fixed set (library) of objects. The problem of identifying which object is present then shares characteristics of the signal detection and parameter estimation problem: which signal is present and what are its parameters? The Reciprocal Basis Set/Direction of Arrival (RBS/DOA) technique is a recently developed technique for object pose determination. It uses a single, comprehensive analytic object model representing a suite of views of an object. Object orientation can be directly established from single 2-D views of the object, without a costly search of the pose parameter space, and without need for the views to be related by a geometric image transformation. This paper describes how one can construct reciprocal basis sets to simultaneously determine object identity and pose from a single 2-D image. Results are presented which demonstrate this ability for a single unknown pose parameter using synthetic and camera-acquired images.

关键词： Visual process modeling Machine vision computer vision technology Robot vision robots Wavefronts Error analysis Image processing Object recognition Signal detection

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Beyond adaptive critic-creative learning for intelligent mobile robots

Beyond adaptive critic-creative learning for intelligent mob...

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conference on intelligent robots and computer vision XX: algorithms, techniques, and Active vision

作者： Liao, XQ Cao, M Hall, E Univ Cincinnati Ctr Robot Res Cincinnati OH 45221 USA

ISBN: (纸本)081944300X

intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new teaming method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning- imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it pe

关键词： reinforcement learning systems adaptive critic intelligent robots heuristic dynamic programming (HDP) dual heuristic programming (DHP) globalized DHP (GDHP)

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