A strategy for identifying, measuring, and duplicating machined parts using an endpoint open loop (EOL) position based, visual servo robot is presented. The procedure is demonstrated using the representative, commerci...
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A strategy for identifying, measuring, and duplicating machined parts using an endpoint open loop (EOL) position based, visual servo robot is presented. The procedure is demonstrated using the representative, commercially important, problem of duplicating keys for automobiles. The tasks completed for this application are: identify the blank type of the original;measure the unique cut pattern;correct deviations;and grind the duplicate.
Three-dimensional multilayer phase gratings (nuclear layers in the human retina) of oscillating cells positioned in the image plane of a monocular optical imaging system transform tight double cones by diffraction and...
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ISBN:
(纸本)081942983X
Three-dimensional multilayer phase gratings (nuclear layers in the human retina) of oscillating cells positioned in the image plane of a monocular optical imaging system transform tight double cones by diffraction and pulsation (quantization) into the reciprocal space behind the grating (Fourier-space in the Fresnel-nearfield). This effect we call OPTORETINA not only guarantees the transformation of the physical stimuli parameters (intensity/wavelength) in the visible spectrum into three chromatically tuned adaptive RGB-color channels (diffraction orders with Brightness-Hue-Saturation aspects) and of object. distances in 3D-space into spatial frequencies or temporal phase differences in reciprocal space (the MULTIDIST grating optical sensors developed at CORRSYS). The 3D-grating, acting as a spatiotemporal frequency and spectral filter, contributes to image pre-processing in Fourier-space. it allows patchwise Fourier-analysis in the Fresnel-nearfield based on weighted Patterson maps of centrosymmetric hexagonal multilayer gratings. Spectral/temporal modulation and spatial frequency analysis seem to be orthogonal to each other as in audition. The OPTORETINA with its cellular diffractive 3D-gratings and their power spectra illustrates a specific part of cortical 4D-spatiotemporal processing. A cortical modulator becomes relevant for temporal coincidence detection and spectral/spatiotemporal correlation in complex image processing, relating multimodal stimulus parameters to internal timing.
robots relying on vision as a primary sensor frequently need to track common objects such as people, cars, and tools in order to successfully perform autonomous navigation or grasping tasks. These objects may comprise...
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robots relying on vision as a primary sensor frequently need to track common objects such as people, cars, and tools in order to successfully perform autonomous navigation or grasping tasks. These objects may comprise many visual parts and attributes, yet image-based tracking algorithms are often keyed to only one of a target's identifying characteristics. In this paper, we present a framework for sharing information among disparate state estimation processes operating on the same underlying visual object. Well-known techniques for joint probabilistic data association are adapted to yield increased robustness when multiple trackers attuned to different visual cues are deployed simultaneously. We also formulate a measure of tracker confidence, based on distinctiveness and occlusion probability, which permits the deactivation of trackers before erroneous state estimates adversely affect the ensemble. We will discuss experiments using color-region, and snake-based tracking in tandem that demonstrate the efficacy of this approach.
Scene segmentation is a pre-processing step for many vision systems. We are concerned with segmentation as a precursor to 3-D scene modeling. Segmentation of a scene for this purpose usually involves dividing an image...
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ISBN:
(纸本)081942983X
Scene segmentation is a pre-processing step for many vision systems. We are concerned with segmentation as a precursor to 3-D scene modeling. Segmentation of a scene for this purpose usually involves dividing an image into areas that are relatively uniform in some value (e.g. intensity, range, or curvature). This single segmented image represents the analogous segmented scene. This paper presents a segmentation method that uses features to indicate boundaries or edges between regions. We incorporate features from multiple image types to obtain an more accurate segmentation of objects or object parts in the scene. Multiple features are not only combined directly to improve segmentation results, but they are also used to guide a smoothing operation. This smoothing technique preserves features representing edges while smoothing noise in the images. The segmentation method is based on applying a watershed algorithm to a fuzzy feature map. A fuzzy feature map being any image containing fuzzy values representing degree of membership in a particular feature class. The first step in obtaining the fuzzy feature map involves smoothing noise from the image pair. We apply an anisotropic diffusion algorithm to both images. This algorithm smooths noise in the images while preserving changes in range, intensity, and surface normal. We create three fuzzy feature maps from the smoothed range and intensity image pair: gradient of the range image, gradient of the intensity image, sind gradient of the surface normal of the range image. We fuse these fuzzy feature maps to create a fuzzy feature map of edges. This map includes both step and crease edges. Where step edges are defined as discontinuities in range and crease edges are discontinuities in surface normal of range. We derive a segmentation from this fuzzy edge map by application of a morphological watershed algorithm. We present results from analysis of real images.
An algorithm consisting of an artificial neural network and phase only match filter (POMF) method to tracking an object in a series of satellite images with variant intensity level is proposed. The notable adaptive re...
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An algorithm consisting of an artificial neural network and phase only match filter (POMF) method to tracking an object in a series of satellite images with variant intensity level is proposed. The notable adaptive resonance theory (ART) neural network is used as a high frequency noise filter for the POMF. The algorithm is examined by means of several satellite images. From the experimental results, the proposed method demonstrates that the performance of POMF can be successfully improved by reducing the high frequent noise of the background in the satellite images.
This paper addresses a method for implementation of some basic geometric transformation, namely rotation and scale, on 1D parallel SIMD computers. Solutions to solve many implementation details such as 2D image scanni...
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This paper addresses a method for implementation of some basic geometric transformation, namely rotation and scale, on 1D parallel SIMD computers. Solutions to solve many implementation details such as 2D image scanning with 1D machine, the floating point arithmetic simulation and an approximation of the transformed pixel spatial co-ordinates are proposed. The proposed approach tolerates up to ±15° rotation and up to ±50% continue scale changes between images. Those transformations can be used for construction of robust matching primitives useful for robot applications. The evaluation of the proposed method, on SYMPATI2, a French 1D parallel computer (designed by CEA,LETI) is reported.
Exploratory research on the design of a modular autonomous mobile robot controller for steering and speed control is described. The high level control of the robot incorporates a fuzzy logic approach. Steering and spe...
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Exploratory research on the design of a modular autonomous mobile robot controller for steering and speed control is described. The high level control of the robot incorporates a fuzzy logic approach. Steering and speed control are achieved using a three-axis Galil motion controller. The steering mechanism and the speed control involve the parallel control of the robot's two front wheels based on decisions made by the upper level fuzzy logic to guide the robot in a desired direction to follow a specific path and avoid obstacles in that path. The steering motors are Electrocraft brush DC motor. The BDC amplifiers are run in the current loop mode. The overall control is supervised by a personal computer through the multi-axis controller. The system has been simulated on Matlab and Simulink and optimal values for the digital gains were achieved for desired control. Testing of these systems has been done in a laboratory setting as well as on an outside track with positive results.
Linear models are a popular tool to characterize the performance of active vision systems. They cannot, however, capture the nonlinear limits of the system performance that arise out of the physical limitations of the...
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Linear models are a popular tool to characterize the performance of active vision systems. They cannot, however, capture the nonlinear limits of the system performance that arise out of the physical limitations of the real system. We examine how the finite field of view and the limited motor torque impose bounds on the linear operation of an active vision system in a fixation task. We derive the bounds by analyzing a real active vision system and measuring its response to repeatable and controllable target motions generated by a robot arm. The knowledge of the operational bounds can guide us in deciding which aspects of the active vision system to improve for better overall performance.
A truly autonomous robot must sense its environment and react appropriately. These issues attain greater importance in an outdoor, variable environment. Previous mobile robot perception systems have relied on hand-cod...
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A truly autonomous robot must sense its environment and react appropriately. These issues attain greater importance in an outdoor, variable environment. Previous mobile robot perception systems have relied on hand-coded algorithms for processing sensor information. Recent techniques involve the use of artificial neural networks to process sensor data for mobile robot guidance. A comparison of a fuzzy logic control for an AGV and a neural network perception is described in this work. A mobile robot test bed has been constructed using a golf cart base. The test bed has a fuzzy logic controller which uses both vision and obstacle information and provides the steering and speed controls to the robot. A feed-forward neural network is described to guide the robot using vision and range data. Suitable criteria for comparison will be formulated and the hand-coded system compared with a connectionist model. A comparison of the two systems, with performance, efficiency and reliability as the criteria, will be achieved. The significance of this work is that it provides comparative tradeoffs on two important robot guidance methods.
This research focuses on applications based on wireless monitoring and robot control, utilizing motion image and augmented reality. These applications include remote services and surveillance-related functions such as...
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This research focuses on applications based on wireless monitoring and robot control, utilizing motion image and augmented reality. These applications include remote services and surveillance-related functions such as remote monitoring. A remote service can be, for example, a way to deliver products at a hospital or old people's home. Due to the mobile nature of the system, monitoring at places with privacy concerns is possible. On the other hand, mobility demands wireless communications. Suitable and present technologies for wireless video transfer are weighted. Identification of objects with the help of Radio Frequency Identifying (RFID) technology and facial recognition results in intelligent actions, for example, where the control of a robot does not require extensive workload from the user. In other words, tasks can be partially autonomous. RFID can be also used in augmentation of the video view with virtual objects. As a real-life experiment, a prototype environment is being constructed that consists of a robot equipped with a video camera and wireless links to the network and multimedia computer.
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