Michael M. Marefat

Geometric reasoning for recognition of three-dimensional object features

A method for extracting manufacturing shape features from the boundary representation of a polyhedral object is presented. In this approach, the depressions of the part are represented as cavity graphs, which are in turn used as a basis for hypothesis generation-elimination. The proposed cavity graphs are an extended representation in which the links reflect the concavity of the intersection between two faces, and the node labels reflect the relative orientation of the faces comprising the depression. Because previous methods have limited success in handling interactions, emphasis is put on automatic analysis of depressions which are formed by the interactions of primitive features. It is shown that although there is a unique subgraph for each primitive feature, every cavity graph does not correspond to a unique set of primitive features. Consequently, since the cavity graph of a depression may not be the union of the representations for the involved primitives, the concept of virtual links for the formal analysis of the depressions based on cavity graphs is introduced. Finally, a suitable method for automatic determination of the virtual links is presented. This method is based on combining topologic and geometric evidences, and uses a combination of Dempster-Shafer decision theory and clustering techniques to reach its conclusions. Experimental results are presented for a number of examples. >

Object-oriented intelligent computer-integrated design, process planning, and inspection

The methodology for developing intelligent integrated computer-aided design and manufacturing systems based on object-oriented principles is discussed. The ways in which the application of these principles affects the nature of these systems are reviewed. The implementation of an automated, intelligent, and flexible computer-integrated-manufacturing (CIM) system prototype using an object-oriented programming environment (Smalltalk-80, Version 4.0) is detailed. A CIM system includes CAD, a process planner, and an inspection planner. Each of these components is discussed individually.<<ETX>>

Error analysis and planning accuracy for dimensional measurement in active vision inspection

This paper discusses the effect of spatial quantization errors and displacement errors on the precision dimensional measurements for an edge segment. Probabilistic analysis in terms of the resolution of the image is developed for 2D quantization errors. Expressions for the mean and variance of these errors are developed. The probability density function of the quantization error is derived. The position and orientation errors of the active head are assumed to be normally distributed. A probabilistic analysis in terms of these errors is developed for the displacement errors. Through integrating the spatial quantization errors and the displacement errors, we can compute the total error in the active vision inspection system. Based on the developed analysis, we investigate whether a given set of sensor setting parameters in an active system is suitable to obtain a desired accuracy for specific dimensional measurements, and one can determine sensor positions and view directions which meet the necessary tolerance and accuracy of inspection.

Automatic construction of process plans from solid model representations

Methods and an implemented system for automatic generation of process plans from the CAD boundary representation of a part are presented. Two problems are addressed: one is the machine understanding of the shape of a part from its low-level boundary representation, and the other is developing a plan based on this semantic information. The architecture of the system at the highest level consists of a solid modeler, a shape description system, an automatic process planner, and the interfaces between them. Cooperative reasoning and combining geometric evidences are used to automatically extract the shape primitives of a part and determine the relations between these primitives from the boundary representation CAD data, thus producing the higher-level semantic information. A case-based planner uses the information produced by the shape description system to construct a conceptual plan for machining the part. Examples illustrate the reasoning performed by the system and show its advantages. >

Bayesian approach for extracting and identifying features

Abstract The paper introduces a new uncertainty reasoning based method for the identification and extraction of manufacturing features from solid model descriptions of objects. A major difficulty faced by previously proposed methods for feature extraction has been the interaction between features. In interacting situations, the representation for various primitive features is nonunique, making their recognition very difficult. The paper develops an approach based on generating, propagating, and combining geometric and topological evidence in a hierarchical belief network for identifying and extracting features. The methodology combines and propagates pieces of evidence to determine a set of corect virtual links to be augmented to the cavity graph representing a depression of the object so that the resulting supergraph can be partitioned to obtain the features of the object. The hierarchical belief network is constructed on the basis of the hypotheses for the potential virtual links. The pieces of evidence, which consist of topological and geometric relationships at different abstraction levels, impacts the belief network through its (amount of) support for different hypotheses. The propagation of the impact of different pieces of evidence updates the beliefs in the network in accordance with the Bayesian probabilistic rules.

Principle Hessian direction based parameter reduction with process variation

As CMOS technology enters the nanometer regime, the increasing process variation is bringing manifest impact on circuit performance. In this paper, we propose a principle Hessian direction (PHD) based parameter reduction approach. This new approach relies on the impact of each parameter on circuit performance to decide whether keeping or reducing the parameter. Compared with the existing principle component analysis (PCA) method, this performance based property provides us a significantly smaller set of parameters after reduction. The experimental results also support our conclusions. In all cases, an average of 53% of reduction is observed with less than 3% error in the mean value and less than 8% error in the variation.

Distributed algorithms for sleep scheduling in wireless sensor networks

It has been found that the sensor nodes dissipate a significant proportion of their energy in redundant sensing and idle listening. The former occurs when multiple sensor nodes perform their sensing activity in the same region. The latter occurs when sensor nodes have their radios switched on awaiting incoming communication from other sensor nodes, but none is received since no sensor node is wanting to communicate with it. Researchers have proposed putting the sensors and/or the radios of sensor nodes to sleep (switch them off) so as to conserve energy. The task of scheduling when the sensors and/or radios need to be in sleep/active mode is referred to as sleep scheduling. Sensor sleeping may result in interesting events being missed by the network or may lead to a lower quality of data being sensed. Radio sleeping may lead to communication delays in the network. In this work we propose several distributed algorithms to perform sensor and radio sleep scheduling in wireless sensor networks while trying to minimize its negative impact

A Dempster-Shafer approach for recognizing machine features from CAD models

Abstract This paper introduces an evidential reasoning-based approach for recognizing and extracting manufacturing features from solid model description of objects. A major difficulty faced by previously proposed methods for feature extraction has been the interaction between features due to non-uniqueness and ambiguousness in feature representation. To overcome this difficulty, we introduce a Dempster–Shafer approach for generating and combining geometric and topologic evidences to identify and extract interacting features. The main contributions of this research include introducing different classes of evidences based on the geometric and topologic relationships at different abstraction levels for effective evidential reasoning and developing the principle of association to overcome the mutual exclusiveness assumption of the Dempster–Shafer theory. Experiments demonstrate the effectiveness of the proposed approach in extracting interacting machine features.

Active visual inspection based on CAD models

This paper is concerned with problems in automated visual inspection of manufactured (particularly machined) components based on their (CAD) design models. In order to achieve the integrated intelligent inspection goals, the authors address several interrelated problems. These problems include: (i) developing hierarchical representation mechanisms to effectively capture the knowledge about geometric entities, their relationships, sensors, and plans, (ii) reasoning mechanisms to determine the different attributes of the different features of an object to be inspected, and the alternative strategies which can be used for inspection of each attribute, (iii) strategies for automated generation of position and viewing angles of the cameras in an active vision system, and for determining the visible entities in each configuration, and (iv) optimization of the constructed plan including minimizing the number of sensor settings and the total distance traveled by an active visual sensor.<<ETX>>

Stereo Camera Pose Determination with Error Reduction and Tolerance Satisfaction for Dimensional Measurements

In this paper, we analyze the error in the dimensional measurement due to localization errors in the image plane of a parallel stereo setup. The mean square error of the dimensional measurements is formulated as the optimality criterion for determining camera poses. To determine optimal poses, a nonlinear program that minimizes the MSE while satisfying the sensor constraints of resolution, focus, field of view, visibility, workspace, and incidence angle constraints is presented. The probability that the measurement errors are within a specified tolerance for this setup is formulated. Finally, we evaluate the performance of the model against real data.