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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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Handling of Split-and-Merge Effects and Occlusions using Feature-Based Probabilistic Data Association

Handling of Split-and-Merge Effects and Occlusions using Fea...

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

作者： Grinberg, Michael Ohr, Florian Fraunhofer Inst Informat & Data Proc IITB D-761313 Karlsruhe Germany

ISBN: (纸本)9780819479327

One of the big challenges in multi-target tracking is the track management and correct data association between measurements and tracks. Major reason for tracking errors are detection failures such as merged, split, incomplete or missed detections as well as clutter-based detections ( phantom objects). Those effects combined with uncertainties in existence and number of objects in the scene as well as uncertainties in their observability and dynamic object state lead to gross tracking errors. In this contribution we present an algorithm for visual detection and tracking of multiple extended targets which is capable of coping with occlusions and split and merge effects. Unlike most of the state-of-the-art approaches we utilize information about the measurements' composition gained through tracking dedicated feature points in the image and in 3D space, which allows us to reconstruct the desired object characteristics from the data even in the case of detection errors due to above-mentioned reasons. The proposed Feature-Based Probabilistic Data Association approach resolves data association ambiguities in a soft threshold-free decision based not only on target state prediction but also on the existence and observability estimation modeled as two additional Markov chains. A novel measurement reconstruction scheme allows for a correct innovation in case of split, merged and incomplete measurements realizing thus a detection-by-tracking approach. This process is assisted by a grid based object representation which offers a lower abstraction level of targets extent and is used for detailed occlusion analysis.

关键词： multitarget tracking 9MTT) feature-based tracking track-before-detect detection-by-tracking probabilistic data association point tracking 6D-vision split and merge handling occlusion handling stereo video environment perception

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active Surveillance of Dynamic Environments using a Multi-Agent System

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IFAC Proceedings Volumes 2010年第16期43卷 13-18页

作者： Annalisa Milella Donato Di Paola Pier Luigi Mazzeo Paolo Spagnolo Marco Leo Grazia Cicirelli Tiziana D'Orazio Institute of Intelligent Systems for Automation National Research Council via Amendola 122/D 70126 Bari Italy

Mobility and multi-functionality have been recognized as being basic requirements for the development of fully automated surveillance systems in realistic scenarios. Nevertheless, problems such as active control of heterogeneous mobile agents, integration of information from fixed and moving sensors for high-level scene interpretation, and mission execution are open. This paper describes recent and current research of the authors concerning the design and implementation of a multi-agent surveillance system, using static cameras and mobile robots. The proposed solution takes advantage of a distributed control architecture that allows the agents to autonomously handle general-purpose tasks, as well as more complex surveillance issues. The various agents can either take decisions and act with some degree of autonomy, or cooperate with each other. This paper presents an overview of the system architecture and of the algorithms involved in developing such an autonomous, multi-agent surveillance system.

关键词： Autonomous mobile robots Cameras computer vision Multi-agent systems Surveillance

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Spatio-temporal modeling of grasping actions

Spatio-temporal modeling of grasping actions

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2010 IEEE/RSJ International Conference on intelligent robots and Systems

作者： Javier Romero Thomas Feix Hedvig Kjellström Danica Kragic Computational Vision and Active Perception Lab KTH Stockholm Sweden Otto Bock Healthcare Gmeinbh Vienna Austria

Understanding the spatial dimensionality and temporal context of human hand actions can provide representations for programming grasping actions in robots and inspire design of new robotic and prosthetic hands. The natural representation of human hand motion has high dimensionality. For specific activities such as handling and grasping of objects, the commonly observed hand motions lie on a lower-dimensional non-linear manifold in hand posture space. Although full body human motion is well studied within computer vision and Biomechanics, there is very little work on the analysis of hand motion with nonlinear dimensionality reduction techniques. In this paper we use Gaussian Process Latent Variable Models (GPLVMs) to model the lower dimensional manifold of human hand motions during object grasping. We show how the technique can be used to embed high-dimensional grasping actions in a lower-dimensional space suitable for modeling, recognition and mapping.

关键词： Grasping Humans Principal component analysis Kernel robots Trajectory Joints

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vision-based lane detection for an autonomous ground vehicle: A comparative field test

Vision-based lane detection for an autonomous ground vehicle...

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Southeastern Symposium on System Theory

作者： Forrest N. Bush Joel M. Esposito US Naval Academy Annapolis MD USA

ISBN: (纸本)9781424456901

We examine the problem of designing computer vision algorithms to autonomously drive an off road vehicle between two lane markings painted on the ground. In this paper we describe field tests used to compare the efficacy of two popular line extractions techniques from the literature: the Hough Transform and the RANSAC Algorithm. Although it is very implementation dependent, we found the Hough Transform to be superior to the RANSAC algorithm in both speed and accuracy for identifying lane markings in the off road environment.

关键词： Vehicle detection Land vehicles Testing Road vehicles Remotely operated vehicles computer vision Mobile robots Global Positioning System Road transportation intelligent vehicles

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vision-based detection for learning articulation models of cabinet doors and drawers in household environments

Vision-based detection for learning articulation models of c...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Jürgen Sturm Kurt Konolige Cyrill Stachniss Wolfram Burgard Autonomous Intelligent Systems Lab Computer Science Department University of Freiburg Germany Willow Garage Inc. Menlo Park CA USA

ISBN: (纸本)9781424450381;9781424450404

Service robots deployed in domestic environments generally need the capability to deal with articulated objects such as doors and drawers in order to fulfill certain mobile manipulation tasks. This however, requires, that the robots are able to perceive the articulation models of such objects. In this paper, we present an approach for detecting, tracking, and learning articulation models for cabinet doors and drawers without using artificial markers. Our approach uses a highly efficient and sampling-based approach to rectangle detection in depth images obtained from a self-developed active stereo system. The robot can use the generative models learned for the articulated objects to estimate their articulation type, their current configuration, and to make predictions about possible configurations not observed before. We present experiments carried out on real data obtained from our active stereo system. The results demonstrate that our technique is able to learn accurate articulation models. We furthermore provide a detailed error analysis based on ground truth data obtained in a motion capturing studio.

关键词： Object detection Cameras Service robots Predictive models Robot vision systems Image segmentation Iterative algorithms Robotics and automation USA Councils Error analysis

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Proceedings of SPIE: intelligent robots and computer vision xxiii: algorithms, techniques, and active vision

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

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intelligent robots and computer vision xxiii: algorithms, techniques, and active vision

The proceedings contain 40 papers. The topics discussed include: face recognition with illumination and pose variations using MINACE filters;retinex software or diffractive-optical correlator hardware: the basis of human color vision?;two and three view geometry based on noisy data: an experimental evaluation;foreground object segmentation from binocular stereo video;a simple approach to a vision-guided unmanned vehicle;design and simulation of a motion controller for a wheeled mobile-robot autonomous navigation;the spectrum enhancement algorithm for feature extraction and pattern recognition;development of written music-recognition system using Java and open source technologies;and kinematics analysis on a spherical robot.

关键词： Face recognition

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Real Time Object Recognition Methodology

Real Time Object Recognition Methodology

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Electronics, Robotics and Automotive Mechanics Conference

作者： M. Peña Cabrera I. López Juárez R. Ríos Cabrera R. Osorio H. Gómez UNAM Mexico Mexico Institute of Research of Applied Mathematics and Systems (IIMAS-UNAM) México CINVESTAV Saltillo México

This paper shows a methodology for on-line recognition and classification of pieces in robotic assembly tasks and its application into an intelligent manufacturing cell. The performance of industrial robots working in unstructured environments can be improved using visual perception and learning techniques The object recognition is accomplished using a neuronal network with FuzzyARTMAP architecture for learning and recognition purposes, which receives a descriptor vector called CFD&POSE as the input. This vector represents an innovative methodology for classification and identification of pieces in robotic tasks, every single stage of the methodology, is described step by step and the proposed algorithms explained. The vector compresses 3D object data from assembly parts and is invariant to scale, rotation and orientation. The approach in combination with the fast learning capability of ART networks indicates the suitability for industrial robot applications as it is shown in experimental results and the possibility to add concatenated information into the descriptor vector to achieve a much more robust methodology.

关键词： Robot sensing systems Assembly computer architecture Machine vision Pixel Artificial neural networks

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intelligent robots and computer vision xxiii: algorithms, techniques, and active vision: 23-25 October, 2005, Boston, Massachusetts, USA (SPIE Conference Proceedings)

Intelligent Robots and Computer Vision XXIII: Algorithms, Te...

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2005年

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Proceedings of SPIE-IS and T Electronic Imaging - intelligent robots and computer vision XXVI: algorithms and techniques

Proceedings of SPIE-IS and T Electronic Imaging - Intelligen...

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intelligent robots and computer vision XXVI: algorithms and techniques

The proceedings contain 28 papers. The topics discussed include: geometric alignment method for large point cloud pairs using sparse overlap areas;a probabilistic approach for the reconstruction of polyhedral objects using shape from shading technique;people detection in crowded scenes using active contour models;homography-based multiple-camera person-tracking;hybrid real-time tracking of non-rigid objects under occlusions;combining a modified vector field histogram algorithm and real-time image processing for unknown environment navigation;development of a vision system for an intelligent ground vehicle;construction engineering robot kit: warfighter experiment;convoy active safety technologies warfighter experiment II;locating and tracking objects by efficient comparison of real and predicted synthetic video imagery;and scene categorization with multi-scale category-specific visual words.

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