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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111-120 订阅

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Real-Time 3D Environment Model for Obstacle Detection and Collision Avoidance with a Mobile Service Robot

Real-Time 3D Environment Model for Obstacle Detection and Co...

引用

27th conference on intelligent robots and computer vision: algorithms and techniques

作者： Kuehnle, J. U. Danzer, M. Verl, A. Bischoff, R. Fraunhofer Inst Mfg Engn & Automat IPA Nobelstr 12 D-70569 Stuttgart Germany KUKA Roboter GmbH D-86165 Augsburg Germany

ISBN: (纸本)9780819479327

In this paper we describe a real-time 3D environment model for obstacle detection and collision avoidance with a mobile service robot. It is fully integrated in the experimental platform DESIRE. Experiments show, that all components perform well and allow for reliable and robust operation of a mobile service robot with actuating capabilities in the presence of obstacles.

关键词： 3D environment model obstacle detection collision avoidance mobile service robots 3D time-of-flight camera general-purpose computation on graphics processing unit

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3D Reconstruction of Underwater Structures

3D Reconstruction of Underwater Structures

引用

IEEE/RSJ International conference on intelligent robots and Systems

作者： Beall, Chris Lawrence, Brian J. Ila, Viorela Dellaert, Frank Georgia Inst Technol Coll Comp Bldg 801 Atlantic Dr Atlanta GA 30332 USA Georgia Inst Technol Atlanta GA 30332 USA UPC CSIC Inst Robot Informat Ind Barcelona Spain

ISBN: (纸本)9781424466757

Environmental change is a growing international concern, calling for the regular monitoring, studying and preserving of detailed information about the evolution of underwater ecosystems. For example, fragile coral reefs are exposed to various sources of hazards and potential destruction, and need close observation. computer vision offers promising technologies to build 3D models of an environment from two-dimensional images. The state of the art techniques have enabled high-quality digital reconstruction of large-scale structures, e.g., buildings and urban environments, but only sparse representations or dense reconstruction of small objects have been obtained from underwater video and still imagery. The application of standard 3D reconstruction methods to challenging underwater environments typically produces unsatisfactory results. Accurate, full camera trajectories are needed to serve as the basis for dense 3D reconstruction. A highly accurate sparse 3D reconstruction is the ideal foundation on which to base subsequent dense reconstruction algorithms. In our application the models are constructed from synchronized high definition videos collected using a wide baseline stereo rig. The rig can be hand-held, attached to a boat, or even to an autonomous underwater vehicle. We solve this problem by employing a smoothing and mapping toolkit developed in our lab specifically for this type of application. The result of our technique is a highly accurate sparse 3D reconstruction of underwater structures such as corals.

关键词： 3d image reconstruction SLAM (robots) autonomous underwater vehicle computer vision computer vision dense reconstruction algorithms image reconstruction image representation sparse representations underwater ecosystems underwater structures underwater vehicles underwater video

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Robust Pipeline Localization for an Autonomous Underwater Vehicle using Stereo vision and Echo Sounder Data

Robust Pipeline Localization for an Autonomous Underwater Ve...

引用

27th conference on intelligent robots and computer vision: algorithms and techniques

作者： Breivik, Goril M. Fjerdingen, Sigurd A. Skotheim, Oystein SINTEF N-0314 Oslo Norway

ISBN: (纸本)9780819479327

Submarine oil and gas pipeline inspection is a highly time and cost consuming task. Using an autonomous underwater vehicle (AUV) for such applications represents a great saving potential. However, the AUV navigation system requires reliable localization and stable tracking of the pipeline position. We present a method for robust pipeline localization relative to the AUV in 3D based on stereo vision and echo sounder depth data. When the pipe is present in both camera images, a standard stereo vision approach is used for localization. Enhanced localization continuity is ensured using a second approach when the pipe is segmented out in only one of the images. This method is based on a combination of one camera with depth information from the echo sounder mounted on the AUV. In the algorithm, the plane spanned by the pipe in the camera image is intersected with the plane spanned by the sea floor, to give the pipe position in 3D relative to the AUV. Closed water recordings show that the proposed method localizes the pipe with an accuracy comparable to that of the stereo vision method. Furthermore, the introduction of a second pipe localization method increases the true positive pipe localization rate by a factor of four.

关键词： stereo vision echo sounder autonomous underwater vehicle AUV robust localization pipe inspection robot vision scene analysis

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Synchronizing real and predicted synthetic video imagery for localization of a robot to a 3D environment

Synchronizing real and predicted synthetic video imagery for...

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27th conference on intelligent robots and computer vision: algorithms and techniques

作者： Lyons, Damian M. Chaudhry, Sirhan Benjamin, D. Paul Fordham Univ Robot & Comp Lab Bronx NY 10458 USA PACE Univ Dept Comp Sci New York NY 10023 USA

ISBN: (纸本)9780819479327

A mobile robot moving in an environment in which there are other moving objects and active agents, some of which may represent threats and some of which may represent collaborators, needs to be able to reason about the potential future behaviors of those objects and agents. In previous work, we presented an approach to tracking targets with complex behavior, leveraging a 3D simulation engine to generate predicted imagery and comparing that against real imagery. We introduced an approach to compare real and simulated imagery using an affine image transformation that maps the real scene to the synthetic scene in a robust fashion. In this paper, we present an approach to continually synchronize the real and synthetic video by mapping the affine transformation yielded by the real/synthetic image comparison to a new pose for the synthetic camera. We show a series of results for pairs of real and synthetic scenes containing objects including similar and different scenes.

关键词： Cognitive robotics robot simulation synthetic video motion detection computer vision robot localization

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Modeling of radial asymmetry in lens distortion facilitated by modern optimization techniques

Modeling of radial asymmetry in lens distortion facilitated ...

引用

27th conference on intelligent robots and computer vision: algorithms and techniques

作者： de Villiers, Jason P. Leuschner, F. Wilhelm Geldenhuys, Ronelle CSIR Meiring Naude Rd Pretoria South Africa Univ Pretoria Dept Elect Elect & Comp Engn Pretoria South Africa

ISBN: (纸本)9780819479327

Most current lens distortion models use only a few terms of Brown's model, which assumes that the radial distortion is dependant only on the distance from the distortion centre, and an additive tangential distortion can be used to correct lens de-centering. This paper shows that the characterization of lens distortion can be improved by over 79% compared to prevailing methods. This is achieved by using modern numerical optimization techniques such as the Leapfrog algorithm, and sensitivity-normalized parameter scaling to reliably and repeatably determine more terms for Brown's model. An additional novel feature introduced in this paper is to allow the distortion to vary not only with polar distance but with the angle too. Two models for radially asymmetrical distortion (i.e. distortion that is dependant on both polar angle and distance) are discussed, implemented and contrasted to results obtained when no asymmetry is modelled. A sample of 32 cameras exhibiting extreme barrel distortion (due to their 6.0mm focal lengths) is used to show that these new techniques can straighten lines to within 7 hundredths of a pixel RMS over the entire image.

关键词： Asymmetry numerical optimization distortion characterization real-time

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Argos: Princeton University's Entry in the 2009 intelligent Ground Vehicle Competition

Argos: Princeton University's Entry in the 2009 Intelligent ...

引用

27th conference on intelligent robots and computer vision: algorithms and techniques

作者： Abiola, Solomon O. Baldassano, Christopher A. Franken, Gordon H. Harris, Richard J. Hendrick, Barbara A. Mayer, Jonathan R. Partridge, Brenton A. Starr, Eric W. Tait, Alexander N. Yu, Derrick D. Zhu, Tony H. Princeton Univ Sch Engn & Appl Sci Princeton NJ 08544 USA

ISBN: (纸本)9780819479327

In this paper, we present Argos, an autonomous ground robot built for the 2009 intelligent Ground Vehicle Competition (IGVC). Discussed are the significant improvements over its predecessor from the 2008 IGVC, Kratos. We continue to use stereo vision techniques to generate a cost map of the environment around the robot. Lane detection is improved through the use of color filters that are robust to changing lighting conditions. The addition of a single-axis gyroscope to the sensor suite allows accurate measurement of the robot's yaw rate and compensates for wheel slip, vastly improving state estimation. The combination of the D* Lite algorithm, which avoids unnecessary re-planning, and the Field D* algorithm, which allows us to plan much smoother paths, results in an algorithm that produces higher quality paths in the same amount of time as methods utilizing A*. The successful implementation of a crosstrack error navigation law allows the robot to follow planned paths without cutting corners, reducing the chance of collision with obstacles. A redesigned chassis with a smaller footprint and a bi-level design, combined with a more powerful drivetrain, makes Argos much more agile and maneuverable compared to its predecessor. At the 2009 IGVC, Argos placed first in the Navigation Challenge.

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

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LandingNav: A precision autonomous landing sensor for robotic platforms on planetary bodies

LandingNav: A precision autonomous landing sensor for roboti...

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27th conference on intelligent robots and computer vision: algorithms and techniques

作者： Katake, Anup Bruccoleri, Christian Singla, Puneet Junkins, John L. StarVis Technol Inc 400 Harvey Mitchell Pkwy SSuite 400 College Stn TX 77845 USA Univ Buffalo Dept Mech & Aerosp Engn Buffalo NY USA Texas A&M Univ Dept Aerosp Engn College Stn TX 77843 USA

ISBN: (纸本)9780819479327

Increased interest in the exploration of extra terrestrial planetary bodies calls for an increase in the number of spacecraft landing on remote planetary surfaces. Currently, imaging and radar based surveys are used to determine regions of interest and a safe landing zone. The purpose of this paper is to introduce LandingNav, a sensor system solution for autonomous landing on planetary bodies that enables landing on unknown terrain. LandingNav is based on a novel multiple field of view imaging system that leverages the integration of different state of the art technologies for feature detection, tracking, and 3D dense stereo map creation. In this paper we present the test flight results of the LandingNav system prototype. Sources of errors due to hardware limitations and processing algorithms were identified and will be discussed. This paper also shows that addressing the issues identified during the post-flight test data analysis will reduce the error down to 1-2%, thus providing for a high precision 3D range map sensor system.

关键词： autonomous planetary landing stereo vision terrain mapping dense range map estimation localization

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Color Image Processing for Date Quality Evaluation

Color Image Processing for Date Quality Evaluation

引用

27th conference on intelligent robots and computer vision: algorithms and techniques

作者： Lee, Dah-Jye Archibald, James K. Brigham Young Univ Provo UT 84602 USA

ISBN: (纸本)9780819479327

Many agricultural non-contact visual inspection applications use color image processing techniques because color is often a good indicator of product quality. Color evaluation is an essential step in the processing and inventory control of fruits and vegetables that directly affects profitability. Most color spaces such as RGB and HSV represent colors with three-dimensional data, which makes using color image processing a challenging task. Since most agricultural applications only require analysis on a predefined set or range of colors, mapping these relevant colors to a small number of indexes allows simple and efficient color image processing for quality evaluation. This paper presents a simple but efficient color mapping and image processing technique that is designed specifically for real-time quality evaluation of Medjool dates. In contrast with more complex color image processing techniques, the proposed color mapping method makes it easy for a human operator to specify and adjust color-preference settings for different color groups representing distinct quality levels. Using this color mapping technique, the color image is first converted to a color map that has one color index represents a color value for each pixel. Fruit maturity level is evaluated based on these color indices. A skin lamination threshold is then determined based on the fruit surface characteristics. This adaptive threshold is used to detect delaminated fruit skin and hence determine the fruit quality. The performance of this robust color grading technique has been used for real-time Medjool date grading.

关键词： machine vision color mapping color grading Medjool date non-contact visual inspection

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On-Line Measurement of Ski-Jumper trajectory: combining Stereo vision and Shape Description

On-Line Measurement of Ski-Jumper trajectory: combining Ster...

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27th conference on intelligent robots and computer vision: algorithms and techniques

作者： Nunner, T. Sidla, O. Paar, G. Nauschnegg, B. Joanneum Res Inst Digital Image Proc Wastiangasse 6 A-8010 Graz Austria SLR Engn EU A-8010 Graz Austria

ISBN: (纸本)9780819479327

Ski jumping has continuously raised major public interest since the early 70s of the last century, mainly in Europe and Japan. The sport undergoes high-level analysis and development, among others, based on biodynamic measurements during the take-off and flight phase of the jumper. We report on a vision-based solution for such measurements that provides a full 3D trajectory of unique points on the jumper's shape. During the jump synchronized stereo images are taken by a calibrated camera system in video rate. Using methods stemming from video surveillance, the jumper is detected and localized in the individual stereo images, and learning-based deformable shape analysis identifies the jumper's silhouette. The 3D reconstruction of the trajectory takes place on standard stereo forward intersection of distinct shape points, such as helmet top or heel. In the reported study, the measurements are being verified by an independent GPS measurement mounted on top of the Jumper's helmet, synchronized to the timing of camera exposures. Preliminary estimations report an accuracy of +/-20 cm in 30 Hz imaging frequency within 40m trajectory. The system is ready for fully-automatic on-line application on ski-jumping sites that allow stereo camera views with an approximate base-distance ratio of 1: 3 within the entire area of investigation.

关键词： ski-jumping active-shape-model calibration stereo-reconstruction online-tracking Eigenshape GPS

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Comparison of Three Control Methods for an Autonomous Vehicle

Comparison of Three Control Methods for an Autonomous Vehicl...

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27th conference on intelligent robots and computer vision: algorithms and techniques

作者： Deshpande, Anup Mathur, Kovid Hall, Ernest Univ Cincinnati Ctr Robot Res Cincinnati OH 45221 USA

ISBN: (纸本)9780819479327

The desirability and challenge of developing a completely autonomous vehicle and the rising need for more efficient use of energy by automobiles motivate the search for an optimum solution to computer control of energy efficient vehicles. The purpose of this paper is to compare three control methods - mechanical, hydraulic and electric that have been used to convert an experimental all terrain vehicle to drive by wire which would eventually act as a test bed for conducting research on various technologies for autonomous operation. computer control of basic operations in a vehicle namely steering, braking and speed control have been implemented and will be described in this paper. The output from a 3 axis motion controller is used for this purpose. The motion controller is interfaced with a software program and WSDK (Windows Servo Design Kit) serves as an intermediate tuning layer for tuning and parameter settings in autonomous operation. The software program is developed in C++ and the voltage signal sent to the motion controller can be varied through the control program for desired results in controlling the steering motor, activating the hydraulic brakes and varying the vehicle's speed. The vehicle has been tested for its basic functionality which includes testing of street legal operations and also a 1000 mile test while running in a hybrid mode. The vehicle has also been tested for control when it is interfaced with devices such as a keyboard, joystick and sensors under full autonomous operation. The vehicle is currently being tested in various safety studies and is being used as a test bed for experiments in control courses and research studies. The significance of this research is in providing a greater understanding of conventional driving controls and the possibility of improving automobile safety skills.

关键词： intelligent autonomous vehicle electrical control hydraulic control mechanical control human interface

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