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检索条件"任意字段=Intelligent Robots and Computer Vision VII 1988"

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High-level planning and low-level control

High-level planning and low-level control

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intelligent robots and computer vision VI 1987

作者： Dean, Thomas Department of Computer Science Brown University Box 1910 ProvidenceRI02912 United States

Research in robotics has primarily progressed along two parallel paths: high-level planning concerned with generating detailed plans from abstract specifications, and low-level control concerned with the role of sensors and manipulators and focusing on the dynamics of realistic domains. In trying to achieve robust performance, researchers interested in low-level control have tried to dispense with complex representations. At the same time, researchers concerned with designing reasonably autonomous robots are convinced that high-level specifications (and their attendant complex representations) are crucial. The fact is different sorts of decision making require representations and computations of varying degrees of complexity and time criticality. The trick is to integrate the different types of decision making and control in a single framework. We describe an architecture for control that makes use of several functionally independent modules each of which has a set of provable properties specific to its particular function. The various modules communicate using representations designed with the particular real-time processing requirements of the communicating modules in mind. The architecture makes it possible for slow modules to communicate with fast modules without interrupting critical behaviors. We believe that our approach will enable us to preserve the desirable properties of the functionally independent modules while at the same time achieving the (relative) singularity of purpose necessary for useful high-level control. © 1988 SPIE. All rights reserved.

关键词： Decision making

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Adaptive novelty filtering for machine vision

Adaptive novelty filtering for machine vision

引用

intelligent robots and computer vision VI 1987

作者： Nessner, Richard A. Bailey, Joseph G. Szu, Harold H. University of New Hampshire E.C.E. Department Kingsbury Hall DurhamNH03824-3591 United States Naval Research Laboratory Tactical Electronic Warfare Code 5709 WashingtonDC20375 United States

The development of an autonomous mobile platform vision system that can adapt to a variety of surroundings by modifying its current memory is an ambitious goal. We believe that to achieve such an ambitious goal it is necessary to look at areas that may seem unconventional to some researchers. Such an area is associative memory. For an autonomous robotic vision system to function adaptively it must be able to respond to a wide variety of visual stimuli, sort out what is new or different from previously stored information, and update its memory taking this new information into account. To compound the problem, this procedure should be invariant to the scale of objects within the scene and to some degree rotations as well. With this in mind we can identify two main functions that are desirable in such a visual system: 1) the ability to identify novel items within a scene;and 2) the ability to adaptively update the system memory. The need for these functions has led to the investigation of a class of filters called Novelty Filters. By use of a coordinate transformation it is possible to specify novelty filters that are invariant to scale and rotational changes. Further, it is then possible to postulate an adaptive memory equation which reflects the adaptive novelty filter for a multiple-channel pattern recognition system. This paper, while not all inclusive, is meant to stimulate further interest as well as report preliminary simulation and mathematical results. © 1988 SPIE. All rights reserved.

关键词： Adaptive filtering

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Integration of multiple sensors in robotic control systems

Integration of multiple sensors in robotic control systems

引用

Third International Symposium on intelligent Control 1988

作者： Lim, S.Y. Luh, J.Y.S. Zheng, Y.F. Dep of Electr & Comput Eng Clemson Univ Clemson SC USA

ISBN: (纸本)0818620129

An intelligent multisensor robotic system consisting of vision, tactile, and force/torque sensors is constructed. An artificial intelligence tool in the form of an expert system shell is included in the system to provide a high-level decision-making tool for the robotic system. The multisensor system consists of a VAX-11/750 supervisory computer, two PUMA-560 robots, a vision system, a work-cell tactile array sensor, an instrumented servo gripper equipped with force/torque and tactile array sensors, a six-component wrist force/torque sensor, and an expert system shell running on an IBM PC. All the components in the system are connected to the supervisory VAX computer. Software and hardware links of the system were also developed. Modularity was emphasized in the system development to permit easy and rapid reconfiguration of the system. A simple sensor fusion experiment was conducted. The experiment was used to test the software and hardware of the entire multisensor system and to illustrate the concept of sensor fusion.

关键词： robots, Industrial

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Rapid recognition out of a large model base using prediction hierarchies and machine parallelism

Rapid recognition out of a large model base using prediction...

引用

intelligent robots and computer vision VI 1987

作者： Burns, J. Brian Kitchen, Leslie J. Computer and Information Science Department University of Massachusetts AmherstMA01003 United States Department of Computer Science University of Western Australia NedlandsWA6009 Australia

An object recognition system is presented to handle the computational complexity posed by a large model base, an unconstrained viewpoint, and the structural complexity and detail inherent in the projection of an object. The design is based on two ideas. The first is to compute descriptions of what the objects should look like in the image, called predictions, before the recognition task begins. This reduces actual recognition to a 2D matching process, speeding up recognition time for 3D objects. The second is to represent all the predictions by a single, combined IS-A and PART-OF hierarchy called a prediction hierarchy. The nodes in this hierarchy are partial descriptions that are common to views and hence constitute shared processing subgoals during matching. The recognition time and storage demands of large model bases and complex models are substantially reduced by subgoal sharing: projections with similarities explicitly share the recognition and representation of their common aspects. A prototype system for the automatic compilation of a prediction hierarchy from a 3D model base is demonstrated using a set of polyhedral objects and projections from an unconstrained range of viewpoints. In addition, the adaptation of prediction hierarchies for use on the UMass Image Understanding Architecture is considered. Object recognition using prediction hierarchies can naturally exploit the hierarchical parallelism of this machine. © 1988 SPIE. All rights reserved.

关键词： Forecasting

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Associative memory synthesis, performance, storage capacity and updating: New heteroassociative memory results

Associative memory synthesis, performance, storage capacity ...

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intelligent robots and computer vision VI 1987

作者： Casasent, David Telfer, Brian Carnegie Mellon University Center for Excellence in Optical Data Processing Department of Electrical and Computer Engineering PittsburghPA15213 United States

The storage capacity, noise performance, and synthesis of associative memories for image analysis are considered. Associative memory synthesis is shown to be very similar to that of linear discriminant functions used in pattern recognition. These lead to new associative memories and new associative memory synthesis and recollection vector encodings. Heteroassociative memories are emphasized in this paper, rather than autoassociative memories, since heteroassociative memories provide scene analysis decisions, rather than merely enhanced output images. The analysis of heteroassociative memories has been given little attention. Heteroassociative memory performance and storage capacity are shown to be quite different from those of autoassociative memories, with much more dependence on the recollection vectors used and less dependence on M/N. This allows several different and preferable synthesis techniques to be considered for associative memories. These new associative memory synthesis techniques and new techniques to update associative memories are included. We also introduce a new SNR performance measure that is preferable to conventional noise standard deviation ratios. © 1988 SPIE. All rights reserved.

关键词： Image analysis

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Range image segmentation via distance slicing

Range image segmentation via distance slicing

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intelligent robots and computer vision VI 1987

作者： Leu, Jia-Guu Sethi, Ishwar K. Department of Computer Science Wayne State University DetroitMI48202 United States

In this paper we present a method to segment a range image into regions which correspond to different object surfaces in the scene. We first obtain an equidistance contour map of the range image from slicing the range image at fixed increment distance values. Pixels along a contour are all at about the same distance from the sensor. We have observed that whenever a contour crosses an object surface edge, we would see direction discontinuity, curvature discontinuity, curvature zero-crossing, or termination of the contour. We call these places the critical points of the contour. We divide a contour into segments at its critical points. Next, we find the two corresponding contour segments on two consecutive slices. Every pair of corresponding contour segments defines a small region in the range image. Thus through registering contour segments in consecutive slices we have partitioned a range image into many small regions. Each region corresponds to a portion of an object surface. The last step is to merge these small regions into larger areas based on whether or not the corresponding scene surface segments of two adjacent regions have similar orientations in the 3-D space. The range image segmentation process is completed when the merging process is done. This approach is fast because it analyzes only the pixels along the equidistance contours and the entire process can be completed in just one pass. © 1988 SPIE. All rights reserved.

关键词： Pixels

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Recovery of superquadrics from 3-D information

Recovery of superquadrics from 3-D information

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intelligent robots and computer vision VI 1987

作者： Boult, Terrance E. Gross, Ari D. Columbia University Department of Computer Science New York CityNY10027 United States

Super-quadrics are a volumetric primitive which can model many objects ranging from cubes to spheres to octahedrons to 8-pointed stars and anything in between. They also can be stretched, bent, tapered and combined with boolean to model a wide range of objects. A restricted class of these have been used as the basic primitives of a volumetric modeling system developed ar SRI. At Columbia, we are interested in using superquadrics as model primitives for computer vision applications because they are flexible enough to allow modeling of many objects, yet they can be described by a small (5-14) number of parameters. In this paper, we discuss our research into the recovery of superellipsoids (a restricted class of superquadrics) from 3-D information, in particular range data. We recall the formulation of superellipsoids in terms of their inside-out function, which divides 3 space into regions inside the volume, on the boundary, and outside the volume. Using this function, we employ a nonlinear least square minimization technique to recover the parameters. We discuss both the advantages of this technique, and some of its major drawbacks. Examples are presented, using both synthetic and actual range-data, where the system successfully recovers negative superquadrics, and superquadrics from sparse data including synthetically generated sparse data from multiple viewpoints. While the system was successful in recovering the examples presented, there are some obvious problems. One of these is the relationship between the inside-out function, and the true least-squared distance of the data from recovered model. We discuss this relationship for three different functions based on the inside-out function. © 1988 SPIE. All rights reserved.

关键词： Recovery

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Shape representation and recognition with depth information

Shape representation and recognition with depth information

引用

intelligent robots and computer vision VI 1987

作者： Gorman, John W. Mitchell, O. Robert Department of Electrical and Computer Engineering University of South Carolina ColumbiaSC29208 United States School of Electrical Engineering Purdue University West LafayetteIN47907 United States

Many global shape recognition techniques, such as moments and Fourier Descriptors, are used almost exclusively with two-dimensional images. It would be desirable to extend these global shape recognition concepts to three dimensional images. Specifically, the concepts associated with Fourier Descriptors will be extended to both three dimensional object representation and recognition and the representation and recognition of objects which are described by depth data. With Fourier Descriptors, two dimensional shape boundaries are described in terms of a set of complex sinusoidal basis functions. Extending this concept to three dimensions, the surface of a shape will be described in terms of a set of three dimensional basis functions. The basis functions which will be used are known as spherical harmonics. Spherical harmonics can be used to describe a function on the surface of the unit sphere. In this application, the function on the unit sphere will describe the shape to be represented. The representation presented here is restricted to the class of objects for which each ray from the origin intersects the surface of the object only once. Basic definitions and properties of spherical harmonics will be discussed. A distance measure for shape discrimination will be derived as a function of the spherical harmonic coefficients for two shapes. The question of representation of objects described by depth data will then be addressed. A functional description for the objects will be introduced, along with methods of normalizing the spherical harmonic coefficients for scale, translation, and orientation so that meaningful library comparisons might be possible. Classification results obtained with a set of simple objects will be discussed. © 1988 SPIE. All rights reserved.

关键词： Harmonic analysis

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Recognizing and locating objects using partial object description generated by feature extraction by demands

Recognizing and locating objects using partial object descri...

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intelligent robots and computer vision VI 1987

作者： Wu, Hsianglung Merat, Francis L. Center for Automation and Intelligent Systems Research Case Western Reserve University 310 Glennan Building ClevelandOH44106 United States

A method called Feature Extraction by Demands (FED) has been developed to generate object descriptions. Objects are described by surface adjacency graphs containing the surface class and the surface equation at each node. Due to occlusion and the use of 2 1/2 D range images the generated object description is frequently partial. This paper describes a new method to generate object hypotheses and to recognize and locate viewed objects using partial descriptions of objects bounded by quadric surfaces. The method proceeds in two phases. In phase one, the object location is estimated from matched surface pairs(between an object description and an object model). Depending upon the surface type, each surface may provide partial or complete location information. As long as the location information calculated from matched surface pairs is consistent, that is passes matching feasibility tests, the object model is a candidate for the viewed object. The consistent partial location information is combined into a more complete object location estimation sequentially. The order of location information to be used in object location estimation is decided by whether a more complete object location can be calculated. If a complete location can be calculated or the object location estimation cannot be further refined the hypothesis is verified by phase two. In phase two, each remaining surface which was not used for object location estimation is searched for a matched model surface and the neighboring relations between surfaces are verified. If the hypothesis passes phase two the model is accepted as a matched model. If a complete object location can be calculated from the accepted hypothesis an optimal object location is calculated. © 1988 SPIE. All rights reserved.

关键词： Feature extraction

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Can shape description be applied to model matching? 6

Can shape description be applied to model matching?

引用

intelligent robots and computer vision VI 1987

作者： Weiss, Richard Dept. of Computer and Information Science University of Massachusetts AmherstMA01003 United States

One approach to object recognition is the matching of two-dimensional contours, which are obtained from the projection of a three-dimensional model, with aggregates of lines extracted from an image. It is necessary to define geometric shape features which aid in the matching and can be used to compute a confidence measure for the match. Some of the standard features include curvature maxima and minima, points of inflection, trihedral vertices, and T-junctions. There has not been much evidence that global transforms such as Fourier series or symmetric axis transform make the solution any easier. What is needed is a hierarchical description which includes smooth curve segments and the types of junctions between them. A geometric grouping process is described which might be able to produce symbolic tokens in an image which could be matched hierarchically with a description from the model. © 1988 SPIE. All rights reserved.

关键词： Object recognition

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