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检索条件"任意字段=Intelligent Robots and Computer Vision XXVIII: Algorithms and Techniques"

共 691 条记录，以下是121-130 订阅

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The 18TH Annual intelligent Ground Vehicle Competition: Trends and Influences for intelligent Ground Vehicle Control

The 18TH Annual Intelligent Ground Vehicle Competition: Tren...

引用

Conference on intelligent robots and computer vision xxviii: algorithms and techniques

作者： Theisen, Bernard L. Frederick, Philip Smuda, William USA TARDEC Warren MI 48397 USA

ISBN: (纸本)9780819484154

The intelligent Ground Vehicle Competition (IGVC) is one of four, unmanned systems, student competitions that were founded by the Association for Unmanned Vehicle Systems International (AUVSI). 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 18 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 75 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 vehicle control engineering education IGVC

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Stereo Matching Based on Two Cameras and One 3D Image Sensor

Stereo Matching Based on Two Cameras and One 3D Image Sensor

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Conference on intelligent robots and computer vision xxviii: algorithms and techniques

作者： Yang, Lu Shao, Xiaowei Shibasaki, Ryosuke Wang, Rongben Univ Tokyo Ctr Spatial Informat Sci Tokyo Japan Jilin Univ Intelligent Vehicle Grp Changchun Peoples R China

ISBN: (纸本)9780819484154

Due to the problems of noise, textureless region and depth discontinuity in stereo matching, a new matching method based on two cameras and one 3D image sensor is proposed in this paper. Though the 3D image sensor can offer a depth map, it has low resolution and much noise. Therefore, it can not be used to 3D reconstruction. However, combining two cameras with one 3D image sensor and regarding the depth map as an initial sparse disparity map is an advantage method in stereo vision matching. This method can largely improve the matching accuracy and decrease the running time. Finally, a dense disparity map can be obtained. The experiment results indicate that the proposed algorithm performs well and the disparity map has more accuracy comparing with existing methods.

关键词： Stereo vision 3D image sensor Area matching Belief propagation Left-and-right consistency Disparity map

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Linear stereo vision based objects detection and tracking using spectral clustering

Linear stereo vision based objects detection and tracking us...

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Conference on intelligent robots and computer vision xxviii: algorithms and techniques

作者： Moqqaddem, Safaa Ruichek, Y. Touahni, R. Sbihi, A. Univ Technol Belfort Montbelaird Syst & Transportat Lab F-90010 Belfort France Ibn Tofail Univ Kenitra LASTID Lab Kenitra Morocco

ISBN: (纸本)9780819484154

cr Objects detection and tracking is a key function for many applications like video surveillance, robotic, intelligent transportation systems, ... etc. This problem is widely treated in the literature in terms of sensors (video cameras, laser range finder, Radar) and methodologies. This paper proposes a new approach for detecting and tracking objects using stereo vision with linear cameras. After the matching process applied to edge points extracted from the images, the reconstructed points in the scene are clustered using spectral analysis. The obtained clusters are then tracked throughout their center of gravity using a Kalman filter and a Nearest Neighbour (NN) based data association algorithm. The approach is tested and evaluated on real data to demonstrate its effectiveness for obstacle detection and tracking in front of a vehicle. This work is a part of a project that aims to develop advanced driving aid systems, supported by the CPER, STIC and Volubilis programs.

关键词： Stereo vision Spectral clustering Tracking Data association

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Phobetor: Princeton University's Entry in the 2010 intelligent Ground Vehicle Competition

<i>Phobetor</i>: Princeton University's Entry in the 2010 In...

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Conference on intelligent robots and computer vision xxviii: algorithms and techniques

作者： Newman, Joshua Zhu, Han Partridge, Brenton A. Szocs, Laszlo J. Abiola, Solomon O. Corey, Ryan M. Suresh, Srinivasan A. Yu, Derrick D. Princeton Univ Dept Elect Engn Princeton NJ 08544 USA Princeton Univ Dept Mech & Aerosp Engn Princeton NJ 08544 USA

ISBN: (纸本)9780819484154

In this paper we present Phobetor, an autonomous outdoor vehicle originally designed for the 2010 intelligent Ground Vehicle Competition (IGVC). We describe new vision and navigation systems that have yielded 3x increase in obstacle detection speed using parallel processing and robust lane detection results. Phobetor also uses probabilistic local mapping to learn about its environment and Anytime Dynamic A* (AD*) to plan paths to reach its goals. Our vision software is based on color stereo images and uses robust, RANSAC-based algorithms while running fast enough to support real-time autonomous navigation on uneven terrain. AD* allows Phobetor to respond quickly in all situations even when optimal planning takes more time, and uses incremental replanning to increase search efficiency. We augment the cost map of the environment with a potential field which addresses the problem of "wall-hugging" and smoothes generated paths to allow safe and reliable path-following. In summary, we present innovations on Phobetor that are relevant to real-world robotics platforms in uncertain environments.

关键词： robotics IGVC stereo vision lane detection IPC cost map path planning

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Design and Evaluation of Multi-Media Security Warnings for the Interaction between Humans and Industrial robots

Design and Evaluation of Multi-Media Security Warnings for t...

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Conference on intelligent robots and computer vision xxviii: algorithms and techniques

作者： Fruth, Jana Kraetzer, Christian Dittmann, Jana Univ Magdeburg D-39016 Magdeburg Germany

ISBN: (纸本)9780819484154

In this document a multi-media security warning design approach for automated production scenarios with industrial robots is introduced. This first approach is based on and adapts design principles of common security programs and a German VDI standard for safety warnings design. We focus on direct human-to-robot interaction scenarios, e. g. the online-programming of industrial robots, because of their potential indirect safety impacts, which could be caused by malicious codes infection of a robots control computer. We designed ten different multi-media security warnings, composed of visual and acoustical information. Visual information of warnings is transported via a traffic light metaphor (symbolizing three different threat levels), different warn icons (symbolizing properties of malicious codes) and instructions icons to programmers or operators and additional textual information. With an acknowledgment button in the middle of the warning, the programmer's confirmation of the reception of the warning is verified. Additionally, three different acoustical signals also indicate the threat level of the warning. Furthermore, an evaluation is presented, which uses concepts known from usability testing (method of loud thinking, questionnaire, time measurement). The aim is to evaluate general design criteria of our developed security warnings and tendency of user perception for further advancement of our warnings design.

关键词： multi-media security warnings human-to-robot interaction evaluation industrial applications

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Augmented reality user interface for mobile ground robots with manipulator arms

Augmented reality user interface for mobile ground robots wi...

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Conference on intelligent robots and computer vision xxviii: algorithms and techniques

作者： Vozar, Steven Tilbury, Dawn M. Univ Michigan Dept Mech Engn Ann Arbor MI 48109 USA

ISBN: (纸本)9780819484154

Augmented Reality (AR) is a technology in which real-world visual data is combined with an overlay of computer graphics, enhancing the original feed. AR is an attractive tool for teleoperated UGV UIs as it can improve communication between robots and users via an intuitive spatial and visual dialogue, thereby increasing operator situational awareness. The successful operation of UGVs often relies upon both chassis navigation and manipulator arm control, and since existing literature usually focuses on one task or the other, there is a gap in mobile robot UIs that take advantage of AR for both applications. This work describes the development and analysis of an AR UI system for a UGV with an attached manipulator arm. The system supplements a video feed shown to an operator with information about geometric relationships within the robot task space to improve the operator's situational awareness. Previous studies on AR systems and preliminary analyses indicate that such an implementation of AR for a mobile robot with a manipulator arm is anticipated to improve operator performance. A full user-study can determine if this hypothesis is supported by performing an analysis of variance on common test metrics associated with UGV teleoperation.

关键词： Augmented Reality User Interface Human Robot Interaction Situational Awareness Unmanned Ground Vehicles (UGVs) Teleoperation Manipulator Arm

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Lane Marking Detection by Extracting White Regions with Predefined Width from Bird's-Eye Road Images

Lane Marking Detection by Extracting White Regions with Pred...

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Conference on intelligent robots and computer vision xxviii: algorithms and techniques

作者： Abe, Sadayuki Shoji, Kenji Toyama, Fubito Miyamichi, Juichi Utsunomiya Univ Grad Sch Engn Utsunomiya Tochigi 3218585 Japan

ISBN: (纸本)9780819484154

Detecting lane markings on roads from in-vehicle camera images is very important because it is one of the fundamental tasks for autonomous running technology and safety driving support system. There are several lane markings detection methods using the width information, but most of these are considered to be insufficient for oblique markings. So, the primary intent of this paper is to propose a detecting lane markings method robust to orientation of markings. In this work, we focus on the width of lane markings standardized by road act in Japan, and propose a method for detecting white lane markings by extracting white regions with constant predefined width from bird's-eye road images after segmentation such as categorical color area one. The proposed method is based on the constrained Delaunay triangulation. The proposed method has a merit that can be measure an exact width for oblique markings on the bird's-eye images because it can be obtained perpendicular width for edge. The effectiveness of the proposed method was shown by experimental results for 187 actual road images taken from an in-vehicle camera.

关键词： Roads Image segmentation Cameras Denoising Safety Imaging systems Standards development Associative arrays Machine vision robots

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FirstAidAssistanceSystem (FAAS) - Improvement of First Aid Measures Using Car2Car-Communication Technology

FirstAidAssistanceSystem (FAAS) - Improvement of First Aid M...

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Conference on intelligent robots and computer vision xxviii: algorithms and techniques

作者： Tuchscheerer, Sven Hoppe, Tobias Kraetzer, Christian Dittmann, Jana Univ Magdeburg D-39106 Magdeburg Germany

ISBN: (纸本)9780819484154

This work's goal is the enhancement of first aid measures directly after car accidents by calling suited first aiders via Car-to-Car (C2C) communication and to assist them providing detailed multimedia support instructions. Our concept combines upcoming C2C communication technologies with established technology, in particular GPS and GSM. After a collision, the proposed FirstAidAssistanceSystem (FAAS) sends a broadcast message using C2C technology according to the IEEE 802.11p standard. All nearby cars (as potential first aiders) are located and at least one nearest candidate (we suggest 3-5) driving towards the accident scene is chosen and notified as first aider. A support guide on his multipurpose display (e. g. the navigation system) provides first aiders with detailed instructions and illustrative tutorials. The paper presents our concept in detail with a discussion of practical evaluation criteria and an introduction of a first test implementation.

关键词： Autonomous multi-vehicle collaboration People and vehicle recognition and tracking Tracking and scene analysis for intelligent vehicles Car-to-car communication Road safety Enhancement of first aid measures First aid assistance

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An Embedded Omnidirectional vision Navigator for Automatic Guided Vehicles

An Embedded Omnidirectional Vision Navigator for Automatic G...

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Conference on intelligent robots and computer vision xxviii: algorithms and techniques

作者： Feng, Weijia Zhang, Baofeng Roning, Juha Cao, Zuoliang Zong, Xiaoning Tianjin Univ State Key Lab Precis Measuring Technol & Instrume Tianjin 300072 Peoples R China Univ Oulu Elect & Informat Engn Dept FIN-4500900 Oulu Finland Infotech Oulu Intelligent Syst Grp FIN-4500900 Oulu Finland Tianjin Univ Technol Sch Mech Engn Tianjin 300384 Peoples R China

ISBN: (纸本)9780819484154

Omnidirectional vision appears the definite significance since its advantage of acquiring full 360 horizontal field of vision information simultaneously. In this paper, an embedded original omnidirectional vision navigator (EOVN) based on fish-eye lens and embedded technology has been researched. Fish-eye lens is one of the special ways to establish omnidirectional vision. However, it appears with an unavoidable inherent and enormous distortion. A unique integrated navigation method which is conducted on the basis of targets tracking has been proposed. It is composed of multi-target recognition and tracking, distortion rectification, spatial location and navigation control. It is called RTRLN. In order to adapt to the different indoor and outdoor navigation environments, we implant mean-shift and dynamic threshold adjustment into the Particle Filter algorithm to improve the efficiency and robustness of tracking capability. RTRLN has been implanted in an independent development embedded platform. EOVN likes a smart crammer based on COMS+FPGA+DSP. It can guide various vehicles in outdoor environments by tracking the diverse marks hanging in the air. The experiments prove that the EOVN is particularly suitable for the guidance applications which need high requirements on precision and repeatability. The research achievements have a good actual applied inspection.

关键词： Omnidirectional vision Fish-eye lens Particle Filter Embedded system Automatic navigation

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Calibration and Rectification Research for Fish-eye lens Application

Calibration and Rectification Research for Fish-eye lens App...

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Conference on intelligent robots and computer vision xxviii: algorithms and techniques

作者： Feng, Weijia Zhang, Baofeng Cao, Zuoliang Zong, Xiaoning Roning, Juha Tianjin Univ State Key Lab Precis Measuring Technol & Instrume Tianjin 300072 Peoples R China Tianjin Univ Technol Sch Elect Engn Tianjin 300384 Peoples R China Univ Oulu Dept Elect & Informat Engn FIN-4500900 Oulu Finland Infotech Oulu Intelligent Syst Grp FIN-4500900 Oulu Finland

ISBN: (纸本)9780819484154

The purpose of this paper aims to promote the application of fish-eye lens. Accurate parameters calibration and effective distortion rectification of an imaging device is of utmost importance in machine vision. Fish-eye lens produces a hemispherical field of view of an environment, which appears definite significant since its advantage of panoramic sight with a single compact visual scene. But fish-eye lens image has an unavoidable inherent severe distortion. The precise optical center is the precondition for other parameters calibration and distortion correction. Therefore, three different optical center calibration methods have been researched for diverse applications. Support Vector Machine (SVM) and Spherical Equidistance Projection Algorithm (SEPA) are integrated to replace traditional rectification methods. SVM is a machine learning method based on the theory of statistics, which have good capabilities of imitating, regression and classification. In this research, SVM provides a mapping table between the fish-eye image and the standard image for human eyes. Two novel training models have been designed. SEPA has been applied to promote the rectification effect of the edge of fish-eye lens image. The validity and effectiveness of our achievements are demonstrated by processing the real images.

关键词： Fish-eye lens calibration distortion rectification SVM spherical equidistance projection algorithm

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