Robert C. Bolles

Bio: Robert C. Bolles is an academic researcher from SRI International. The author has contributed to research in topics: Feature (computer vision) & Epipolar geometry. The author has an hindex of 24, co-authored 64 publications receiving 25498 citations. Previous affiliations of Robert C. Bolles include Artificial Intelligence Center.

AL, a programming system for automation.

Abstract: AL is a high-level programming system for specification of manipulatory tasks such as assembly of an object from parts. AL includes an ALGOL-like source language, a translator for converting programs into runnable code, and a runtime system for controlling manipulators and other devices. The system includes advanced features for describing individual motions of manipulators, for using sensory information, and for describing assembly algorithms in terms of common domain-specific primitives. This document describes the design of AL, which is currently being implemented as a successor to the Stanford WAVE system.

3DPO: A Three-Dimensional Part Orientation System.

Abstract: A system that recognizes objects in a jumble, verifies them, and then determines some essential configurational information, such as which ones are on top, is presented. The approach is to use three-dimensional models of the objects to find them in range data. The matching strategy starts with a distinctive edge feature, such as the edge at the end of a cylindrical part, and then “grows” a match by adding compatible features, one at a time. (The order of features to be considered is predetermined by an interactive, off-line feature-selection process.) Once a sufficient number of compatible features has been detected to allow a hypothesis to be formed, the verification procedure evaluates it by comparing the measured range data with data predicted according to the hypothesis. When all the objects in the scene have been hypothesized and verified in this manner, a configuration-understanding procedure determines which objects are on top of others by analyzing the patterns of range data predicted from all the hypotheses. Experimental results of the system’s performance in recognizing and locating castings in a bin are presented.

Verification vision for programmable assembly

Abstract: This paper is a condensed version of the author's thesis [Bolles 1976], which investigates a subclass of visual information processing referred to as verification vision (abbreviated VV). VV uses a model of a scene to locate objects of interest in a picture of the scene. The characteristics that distinguish VV from the other types of visual information processing are: (1) the system has a great deal of prior knowledge about the type, placement, and appearance of the objects that form the scene and (2) the goal is to verify and refine the location of one or more objects in the scene. VV includes a significant portion of the visual feedback tasks required within programmable assembly. For example, locating a screw hole and determining the relative displacement between a screw and the screw hole are both VV tasks. Two types of VV tasks are discussed in the thesis: inspection and location. This paper only discusses location tasks, but essentially the same capabilities are required for both types of tasks. This paper describes (1) a structure for a VV system that makes it easier for programmers who are not experts in computer vision to program VV feedback, and (2) a set of combination rules that are capable of using the results of several different types of operators to estimate the confidences and precisions that are necessary within VV. An interactive VV system based upon these ideas has been implemented. It helps the programmer select potentially useful operator/feature pairs, provides a training session to gather statistics on the behavior of the operators, automatically ranks the operator/feature pairs according to their expected contributions, and performs the desired task. The VV system has also been interfaced to the AL control system for the mechanical arms and has been tested on tasks that involve a combination of touch, force, and visual feedback.

The use of sensory feedback in a programmable assembly system.

Abstract: This article describes an experimental, automated assembly system which uses sensory feedback to control an electro-mechanical arm and TV camera. Visual, tactile, and force feedback are used to improve positional information, guide manipulations, and perform inspections. The system has two phases: a ''planning'' phase in which the computer is programmed to assemble some object, and a ''working'' phase in which the computer controls the arm and TV camera in actually performing the assembly. The working phase is designed to be run on a mini-computer. The system has been used to assemble a water pump, consisting of a base, gasket, top, and six screws. This example is used to explain how the sensory data is incorporated into the control system. A movie showing the pump assembly is available from the Stanford Artificial Intelligence Laboratory.

Perceptual organization and the curve partitioning problem

Abstract: I INTRODUCTION A basic attribute of the human visual system is its ability to group elements of a perceived scene or visual field into meaningful or coherent clusters; in addition to clustering or partitioning, the visual system generally imparts structure and often a semantic interpretation to the data. In spite of the apparent existence proof provided by human vision, the general problem of scene partitioning remains unsolved for computer vision. Part of the difficulty resides In the fact that it is not clear to what extent semantic knowledge (e.g., recognizing the appearance of a straight line or some letter of the English alphabet), as opposed to generic criteria (e.g., grouping scene elements on the basis of geometric proximity), is employed in examples of human performance. Since, at present, we cannot hope to duplicate human competence in semantic interpretation, it would be desirable to find a task domain in which the Influence of semantic knowledge is limited. In such a domain it might be possible to discover the generic criteria employed by the human visual system. One of the main goals of the research effort described in this paper is to find a set of generic rules and models that will permit a machine to duplicate human performance in partitioning planar curves. II THE PARTITIONING PROBLEM Even If we are given a problem domain in which explicit semantic cues are missing, to what extent Is partitioning dependent on the purpose, vocabulary, data representation, and past experience of the "partitioning instrument," as opposed to being a search for context Independent "intrinsic structure" in the data? We argue that rather than having a unique formulation, the partitioning problem must be paramaterized along a number of basic dimensions. In the remainder of this section we enumerate some of these dimensions and discuss their relevance. A. Intent (Purpose) of the Partitioning Task In the experiment described in Figure 1, human subjects were presented with the task of partitioning a set of two-dimensional curves with respect to three different objectives: (1) choose a set of contour points that best mark those locations at which curve segments produced by different processes were "glued" together; (2) choose a set of contour points that best allow one to reconstruct the complete curve; (3) choose a set of contour points that would best allow one to distinguish the given curve from others. Each person was given only one of the …

Gapped BLAST and PSI-BLAST: a new generation of protein database search programs.

Abstract: The BLAST programs are widely used tools for searching protein and DNA databases for sequence similarities. For protein comparisons, a variety of definitional, algorithmic and statistical refinements described here permits the execution time of the BLAST programs to be decreased substantially while enhancing their sensitivity to weak similarities. A new criterion for triggering the extension of word hits, combined with a new heuristic for generating gapped alignments, yields a gapped BLAST program that runs at approximately three times the speed of the original. In addition, a method is introduced for automatically combining statistically significant alignments produced by BLAST into a position-specific score matrix, and searching the database using this matrix. The resulting Position-Specific Iterated BLAST (PSIBLAST) program runs at approximately the same speed per iteration as gapped BLAST, but in many cases is much more sensitive to weak but biologically relevant sequence similarities. PSI-BLAST is used to uncover several new and interesting members of the BRCT superfamily.

A method for registration of 3-D shapes

Abstract: The authors describe a general-purpose, representation-independent method for the accurate and computationally efficient registration of 3-D shapes including free-form curves and surfaces. The method handles the full six degrees of freedom and is based on the iterative closest point (ICP) algorithm, which requires only a procedure to find the closest point on a geometric entity to a given point. The ICP algorithm always converges monotonically to the nearest local minimum of a mean-square distance metric, and the rate of convergence is rapid during the first few iterations. Therefore, given an adequate set of initial rotations and translations for a particular class of objects with a certain level of 'shape complexity', one can globally minimize the mean-square distance metric over all six degrees of freedom by testing each initial registration. One important application of this method is to register sensed data from unfixtured rigid objects with an ideal geometric model, prior to shape inspection. Experimental results show the capabilities of the registration algorithm on point sets, curves, and surfaces. >

Multiple View Geometry in Computer Vision.

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A taxonomy and evaluation of dense two-frame stereo correspondence algorithms

Abstract: Stereo matching is one of the most active research areas in computer vision. While a large number of algorithms for stereo correspondence have been developed, relatively little work has been done on characterizing their performance. In this paper, we present a taxonomy of dense, two-frame stereo methods designed to assess the different components and design decisions made in individual stereo algorithms. Using this taxonomy, we compare existing stereo methods and present experiments evaluating the performance of many different variants. In order to establish a common software platform and a collection of data sets for easy evaluation, we have designed a stand-alone, flexible C++ implementation that enables the evaluation of individual components and that can be easily extended to include new algorithms. We have also produced several new multiframe stereo data sets with ground truth, and are making both the code and data sets available on the Web.