Robust range estimation is one of the most important tasks in mobile robotics. This paper presents a new optical arrangement for utilizing the previously known 'depth from defocus' principle. The arrangement m...
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ISBN:
(纸本)0819423068;9780819423061
Robust range estimation is one of the most important tasks in mobile robotics. This paper presents a new optical arrangement for utilizing the previously known 'depth from defocus' principle. The arrangement makes it possible to apply standard video lenses and camera modules for making a compact range camera system. Real-time processing is made possible with a single-board DSP card.
To be completely successful, robots need to have reliable perceptual systems that are similar to human vision. It is hard to use geometric operations for processing of natural images. Instead, the brain builds a relat...
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ISBN:
(纸本)081945561X
To be completely successful, robots need to have reliable perceptual systems that are similar to human vision. It is hard to use geometric operations for processing of natural images. Instead, the brain builds a relational network-symbolic structure of visual scene, using different clues to set up the relational order of surfaces and objects with respect to the observer and to each other. Feature, symbol, and predicate are equivalent in the biologically inspired Network-Symbolic systems. A linking mechanism binds these features/symbols into coherent structures, and image converts from a "raster" into a "vector" representation. View-based object recognition is a hard problem for traditional algorithms that directly match a primary view of an object to a model. In Network-Symbolic Models, the derived structure, not the primary view, is a subject for recognition. Such recognition is not affected by local changes and appearances of the object as seen from a set of similar views. Once built, the model of visual scene changes slower then local information in the visual buffer. It allows for disambiguating visual information and effective control of actions and navigation via incremental relational changes in visual buffer. Network-Symbolic models can be seamlessly integrated into the NIST 4D/RCS architecture and better interpret images/video for situation awareness, target recognition, navigation and actions.
Autonomous systems that navigate through unknown and unstructured environments must solve the egomotion estimation problem. Fusing the information from many different sensors makes this motion estimation more stable, ...
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ISBN:
(纸本)081945561X
Autonomous systems that navigate through unknown and unstructured environments must solve the egomotion estimation problem. Fusing the information from many different sensors makes this motion estimation more stable, but requires that the relative position and orientation of these sensors be known. Self-calibration algorithms are the most useful for this calibration problem because the do not require any known feature in the environment and can be used during system operation. Here we give geometric constraints, the coherent motion constraints, that allow a framework for the development of self-calibration algorithms for a heterogeneous sensor system (such as cameras, laser range finders, and odometry). If, for all sensors, a conditional probability density function can be defined to relate sensor measurements to the sensor motion, then the coherent motion constraints allows a maximum likelihood formulation of the sensor calibration problem. We present complete algorithms here for the case of a camera and laser range finder, in the case of both discrete and differential motions.
We consider analog neural network implementations (using VLSI or optical technologies) with limited accuracy and various noise and nonlinearity error sources. algorithms and techniques to achieve high performance (goo...
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ISBN:
(纸本)0819407453
We consider analog neural network implementations (using VLSI or optical technologies) with limited accuracy and various noise and nonlinearity error sources. algorithms and techniques to achieve high performance (good recognition P'c% and large storage capacity) on such systems are considered. The adaptive clustering neural net (ACNN) and robust Ho-Kashyap (HK-2) associative processor (AP) are the neural networks considered in detail.
Fov improving underwater visibility for robots. a method using special intervallic series of light pulses, and two acts of emitting and receiving are performed by two special designed optical shutters and the control ...
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The purpose of this paper is to introduce a cost-effective way to design robot vision and control software using Matlab for an autonomous robot designed to compete in the 2004 intelligent Ground Vehicle Competition (I...
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ISBN:
(纸本)081945561X
The purpose of this paper is to introduce a cost-effective way to design robot vision and control software using Matlab for an autonomous robot designed to compete in the 2004 intelligent Ground Vehicle Competition (IGVC). The goal of the autonomous challenge event is for the robot to autonomously navigate an outdoor obstacle course bounded by solid and dashed lines on the ground. Visual input data is provided by a DV camcorder at 160 x 120 pixel resolution. The design of this system involved writing an image-processing algorithm using hue, satuaration, and brightness (HSB) color filtering and Matlab image processing functions to extract the centroid, area, and orientation of the connected regions from the scene. These feature vectors are then mapped to linguistic variables that describe the objects in the world environment model. The linguistic variables act as inputs to a fuzzy logic controller designed using the Matlab fuzzy logic toolbox, which provides the knowledge and intelligence component necessary to achieve the desired goal. Java provides the central interface to the robot motion control and image acquisition components. Field test results indicate that the Matlab based solution allows for rapid software design, development and modification of our robot system.
Scenes of polyhedral objects may be accurately represented in 2-D using line sketches. An aim of low level image processing is to generate useful binary images from grey scale images. The binary images generated by en...
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ISBN:
(纸本)0819413208
Scenes of polyhedral objects may be accurately represented in 2-D using line sketches. An aim of low level image processing is to generate useful binary images from grey scale images. The binary images generated by enhancement/threshold edge detectors are usually unrefined outlines of the underlying 3-D scene. Such images must be further processed to isolate and identify region boundaries; which, in the case of polyhedra, consist of line segments. The intersection or connection points of these line segments are known as vertices or corners. The work reported in this paper employs a decision theoretic approach to detect vertices in grey scale images.
Spherical robot, rolling by altering its' barycenter with the inside actuating device, has a spherical or spheroid housing, the motivity of which is supplied by the friction force between the housing and the groun...
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Spherical robot, rolling by altering its' barycenter with the inside actuating device, has a spherical or spheroid housing, the motivity of which is supplied by the friction force between the housing and the ground while it rolling. Particular attention is paid to the research of spherical robot in recent years. This paper presents a new omnidirectional bi-driver spherical robot droved by two motors that directly drive the balancer to rotate about two orthogonal axes. The spherical robot is a nonholonomic system with 3 DOF while it rolls on the ground, so the spherical presented in this paper is a nonholonomic under-actuated system, featuring omnidirectional movement, simple configuration, and so on.
Shape classification via linear granulometric moments is examined for patterns suffering varying degrees of edge noise. It is seen that recognition is quite poor even for modest amounts of noise and remains poor even ...
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ISBN:
(纸本)0819413208
Shape classification via linear granulometric moments is examined for patterns suffering varying degrees of edge noise. It is seen that recognition is quite poor even for modest amounts of noise and remains poor even when the patterns are first filtered by a close-open filter. Recognition accuracy is greatly improved, for both unfiltered and filtered images, by employing exterior granulometries. These are constructed by applying the various linear structuring-element sequences to the corresponding linear convex hulls of the noisy patterns. The resulting granulometric distributions are then not corrupted by noise-induced probability mass at the left of the pattern spectrum, thereby greatly diminishing the detrimental effects on the pattern spectrum moments.
We discuss the uniqueness of 3D shape recovery of a polyhedron from a single shading image, and propose an approach to uniquely determine the concave shape solution by using interreflections as a constraint. We show t...
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ISBN:
(纸本)0819423068;9780819423061
We discuss the uniqueness of 3D shape recovery of a polyhedron from a single shading image, and propose an approach to uniquely determine the concave shape solution by using interreflections as a constraint. We show that if interreflection distribution is not considered, multiple convex shape solutions usually exist for a pyramid with three or more visible facets. However, if interreflection distribution is used as a constraint to limits the shape of polyhedron, polyhedral shape can be uniquely determined. Interreflections, which were considered to be deleterious in conventional approaches, are an important constraint for shape-from-shading.
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