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

共 373 条记录，以下是121-130 订阅

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Comparison of Three Control Methods for an Autonomous Vehicle

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

引用

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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Real Time Object Recognition Methodology

Real Time Object Recognition Methodology

引用

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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VideoTrek: A vision System for a Tag-along Robot

VideoTrek: A Vision System for a Tag-along Robot

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IEEE-computer-Society conference on computer vision and Pattern Recognition Workshops

作者： Naroditsky, Oleg Zhu, Zhiwei Das, Aveek Samarasekera, Supun Oskiper, Taragay Kumar, Rakesh Sarnoff Corp Princeton NJ 08540 USA

ISBN: (纸本)9781424439928

We present a system that combines multiple visual navigation techniques to achieve GPS-denied, non-line-of-sight SLAM capability for heterogeneous platforms. Our approach builds on several layers of vision algorithms, including sparse frame-to-frame structure from motion (visual odometry), a Kalman filter for fusion with inertial measurement unit (IMU) data and a distributed visual landmark matching capability with geometric consistency verification. We apply these techniques to implement a tag-along robot, where a human operator leads the way and a robot autonomously follows. We show results for a real-time implementation of such a system with real field constraints on CPU power and network resources.

关键词： intelligent robots

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Autonomous altitude estimation of a UAV using a single onboard camera

Autonomous altitude estimation of a UAV using a single onboa...

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2009 IEEE/RSJ International conference on intelligent robots and Systems

作者： Anoop Cherian Jon Andersh Vassilios Morellas Nikolaos Papanikolopoulos Bernard Mettler Department of Computer Science University of Minnesota Minneapolis MN USA Department of AeroSpace Engineering University of Minnesota Minneapolis MN USA

Autonomous estimation of the altitude of an Unmanned Aerial Vehicle (UAV) is extremely important when dealing with flight maneuvers like landing, steady flight, etc. vision based techniques for solving this problem have been underutilized. In this paper, we propose a new algorithm to estimate the altitude of a UAV from top-down aerial images taken from a single on-board camera. We use a semi-supervised machine learning approach to solve the problem. The basic idea of our technique is to learn the mapping between the texture information contained in an image to a possible altitude value. We learn an over complete sparse basis set from a corpus of unlabeled images capturing the texture variations. This is followed by regression of this basis set against a training set of altitudes. Finally, a spatio-temporal Markov Random Field is modeled over the altitudes in test images, which is maximized over the posterior distribution using the MAP estimate by solving a quadratic optimization problem with L1 regularity constraints. The method is evaluated in a laboratory setting with a real helicopter and is found to provide promising results with sufficiently fast turnaround time.

关键词： Unmanned aerial vehicles Machine learning Helicopters intelligent robots USA Councils Robot vision systems Smart cameras computer science Machine learning algorithms Markov random fields

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3D feature based mapping towards mobile robots' enhanced performance in rescue missions

3D feature based mapping towards mobile robots' enhanced per...

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2009 IEEE/RSJ International conference on intelligent robots and Systems

作者： Paloma de la Puente Diego Rodriguez-Losada Alberto Valero Fernando Matia Intelligent Control Group Universidad Politecnica de Madrid Madrid Spain

This paper presents a feature based 3D mapping approach with regard to obtaining compact models of semi-structured environments such as partially destroyed buildings where mobile robots are to carry out rescue activities. To gather the 3D data, we use a laser scanner, employing a nodding data acquisition system mounted on both real and simulated robots. Our segmentation algorithm comes up from the integration of computer vision techniques, allowing for a fast separation of points corresponding to different, not necessarily planar, surfaces. The subsequent extraction of geometrical features out of each region's points is done by means of least-squares fitting. A Maximum Incremental Probability algorithm formulated upon the Extended Kalman Filter provides 6D localization and produces a map of planar patches with a convex-hull based representation. Scenarios from the Unified System for Automation and Robot Simulation (USARSim), including world models from past RoboCup Rescue editions' arenas, have been utilized to conduct some of our experiments.

关键词： Mobile robots Robotics and automation intelligent robots Laser modes Feature extraction Solid modeling Iterative algorithms Iterative closest point algorithm Simultaneous localization and mapping Noise measurement

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Simultaneous object recognition and position tracking for robotic applications

Simultaneous object recognition and position tracking for ro...

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International conference on Mechatronics (ICM)

作者： Dimitris Aristos Spyros Tzafestas Intelligent Robotics and Automation Laboratory School of Electrical and Computer Engineering National and Technical University of Athens Athens Greece

Object recognition techniques are well known in the field of machine vision, and aim at the classification of certain observed rigid objects based on the information acquired by a specific sensor. These techniques can either be performed in the 2D image space by simply applying suitable image processing algorithms, or in the real world 3D space by performing surface reconstruction of the object's surface and comparing it with a database of known CAD data. This paper presents a combination of techniques which not only recognize and categorize the observed rigid objects but also compute their 3D pose (position and orientation) with respect an industrial robot's workspace frame. This task is very useful in the field of robotics as it allows an industrial robot to simultaneously recognize and follow the displacements of a specific rigid object, among other objects that may co-exist in the same environment.

关键词： Object recognition Service robots Orbital robotics Surface reconstruction Robot sensing systems Machine vision Image processing Image reconstruction Image databases Object oriented databases

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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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