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ADVANCES IN computerS 1991年第C期32卷 105-148页

作者： TRIVEDI, MM CHEN, CX Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department The University of Tennessee Knoxville Tennessee

Intelligent robotic systems should be capable of performing a range of complex tasks in unstructured and dynamic environments. This chapter discusses a number of important items associated with intelligent robots, role of vision sensing in intelligent robotics, and architecture for the design of an intelligent robot. The chapter also describes the computational task hierarchy that governs a model-based robot vision system, and presents a detailed tutorial on two important components of this hierarchy: image segmentation and matching. The main capabilities that intelligent robotic systems should possess include ability for perception of their environment, planning of their actions, and execution of the planned action. The two important components of a model-based vision system are image segmentation and the matching module. A procedure that allows transformation of 2D image coordinates into 3D world coordinates is also discussed in the chapter. The architecture and control aspects of an integrated sensor-based robotic system consist of six modules: supervisor, task planner, perception, motor, user interface, and knowledge-base. Intelligent, sensor-driven systems pose many challenging basic-research problems from a broad range of scientific and technological disciplines; however, there are many important application areas where such systems would be of significant value and utility, including hazardous environments such as nuclear plants, underwater, and space as well as many industrial-automation tasks. Recent advancements in the VLSI, computer-architectures, sensor-and robot-hardware, and artificial-intelligence fields may aid to the development of robust, practical, and cost-effective intelligent robotic systems for a wide variety of applications.

关键词： robotics

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Active exploration of robotic workcell

Active exploration of robotic workcell

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IEEE International Conference on Systems, Man and Cybernetics

作者： H.P. Gadagkar M.M. Trivedi Computer Vision and Robotics Research Laboratory Electrical and Computer Engineering Department University of Tennessee Knoxville TN USA

A description is given of research efforts directed towards the development of an active exploration system performing acquisition, processing, and integration of sensory inputs from vision, point laser range, tactile, and force/torque sensors. An attempt is made to bring out the rationale that robotic workcell exploration can benefit by utilizing noncontact (e.g., vision, range, and proximity) as well as contact (e.g., tactile and force/torque) sensors while accomplishing tasks such as object identification, object localization, object grasping and object manipulation. The experimental results presented indicate that the rationale utilized in the design of the multisensory robotic active exploration scheme can work successfully.< >

关键词： Robot sensing systems Sensor phenomena and characterization Robot vision systems Force sensors Torque Tactile sensors Humans Capacitive sensors computer vision Laboratories

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Shape from focus: an effective approach for rough surfaces

Shape from focus: an effective approach for rough surfaces

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IEEE International Conference on robotics and Automation (ICRA)

作者： S.K. Nayar Y. Nakagawa The Robotics Institute Department of Electrical and Computer Engineering Carnegie Mellon University Pittsburgh PA USA Production Engineering Research Laboratory Hitachi and Limited Yokohama Kanagawa Japan

Two algorithms for depth estimation are presented. The first algorithm simply looks for the focus level that maximizes the focus measure at each image point. The second algorithm uses a Gaussian model to interpolate the focus measures to obtain more accurate depth estimates. The algorithms were implemented and tested on surfaces of different roughness and reflectance properties. The results indicate that the shape-from-focus method may be applied to a variety of industrial vision problems.< >

关键词： Shape Rough surfaces Surface roughness Focusing Frequency Image sensors Image analysis Layout Robots Image sequences

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Mean field theory and MT neurons

Mean field theory and MT neurons

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IEEE International Conference on Systems, Man and Cybernetics

作者： A. Dobbins S.W. Zucker Computer Vision and Robotics Laboratory Department of Electrical Engineering McGill University Montreal QUE Canada Canadian Institute for Advanced Research Montreal QUE Canada

The problem of obtaining reliable estimates of the optic flow field and its variation is discussed. It is argued that circuitry in the middle temporal (MT) visual area is arranged to provide mean field approximations of the optical flow field, that is, the maximal neighborhood over which the local field can be well-approximated as uniform, parallel translation. In addition, the way the mean field approximation varies with neighborhood size and position is informative about the variation of the flow field. It is shown how receptive fields can be synthesized to represent the first-order differential information about the flow field. The same ideas are applicable to the binocular disparity vector field, and lead one to predict the existence of extrastriate neurons that are specialized for the local shear and stretch of the disparity and motion vector fields.< >

关键词： Neurons Image motion analysis Circuits computer architecture computer vision Robot vision systems Laboratories Shape Optical devices Retina

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EARLY ORIENTATION SELECTION—INFERRING TRACE, TANGENT, AND CURVATURE FIELDS

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International Journal of Pattern Recognition and Artificial Intelligence 1988年第3期2卷 443-457页

作者： STEVEN W. ZUCKER Canadian Institute for Advanced Research Computer Vision and Robotics Laboratory Department of Electrical Engineering McGill University Montréal Québec Canada

Orientation selection is the inference of orientation information out of images. It is one of the foundations on which other visual structures are built, since it must precede the formation of contours out of pointillist data and surfaces out of surface markings. We take a differential geometric view in defining orientation selection and develop algorithms for actually doing it. The goal of these algorithms is formulated in mathematical terms as the inference of a vector field of tangents (to the contours), and the algorithms are studied in both abstract and computational forms. They are formulated as matching problems, and algorithms for solving them are reduced to biologically plausible terms. We show that two different matching problems are necessary, the first for 1-dimensional contours (which we refer to as Type I processes) and the second for 2-dimensional flows (or Type II processes).

关键词： computer vision Orientation selection Curve detection Relaxation Edge detection Texture

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Deriving course 3D models of objects

Deriving course 3D models of objects

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Conference on computer vision and Pattern Recognition (CVPR)

作者： F.P. Ferrie M.D. Levine Computer Vision and Robotics Laboratory Department of Electrical Engineering McGill University Montreal QUE Canada

Much of the emphasis in computer vision research has been on recognizing objects. However, in order to perform tasks such as manipulating and avoiding collisions with objects, one needs to consider how to derive appropriate three-dimensional descriptions of objects from available sensor data. A description is given of a computational approach that has been successful in deriving renditions of shaded images in terms of volumetric primitives such as ellipsoids and cylinders.< >

关键词： Ellipsoids computer vision Shape Robot vision systems Laboratories Sensor phenomena and characterization Engine cylinders Robustness Eyes Collision avoidance

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Robotically assisted field material handling using combined visual/acoustic sensing system

Robotically assisted field material handling using combined ...

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1988 International Conference on Industrial Electronics: robotics and vision, IECON 1988

作者： Luo, Ren C. Jang, Jong W. Sousk, Steve Keller, Harry Robotics and Intelligence System Laboratory Department of Electrical and Computer Engineering North Carolina State University RaleighNC27695-7911 United States U. S. Army Belvoir Research Development and Engineering Center United States

A robotically assisted field material handling system designed for loading and unloading of a planar pallet with a forklift in unstructured field environment is'presented The system uses combined acoustic/visual sensing data to define the position/orientation of the pallet and to determine the specific locations of the two slots of the pallet, so that the forklift can move close to the slot and engage it for transport. In order to reduce the complexity of the material handling operation, we have developed a method based on the integration of 2-D range data of Poraloid ultrasonic sensor along with 2-D visual data of an optical camera. Data obtained from the two separate sources complements each other and is used in an efficient algorithm to control this robotically assisted field material handling system. Range data obtained from two linear scannings is used to determine the pan and tilt angles of of a pallet using least mean square method. Then, 2-D visual data is used to determine the swing angle and. © 1988 IEEE.

关键词： Pallets

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Region grouping from a range image

Region grouping from a range image

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Conference on computer vision and Pattern Recognition (CVPR)

作者： J.H. Han R.A. Volz Robotics Research Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann Arbor MI USA

A novel method is presented for grouping range image regions such that each group of regions represents a meaningful part of an object. The set of regions, defined as a convex region set (CRS), is obtained by analyzing the boundary types between a pair of regions. The boundary types are classified as convex, concave and jump boundaries. If two regions share a convex boundary it is assumed that they are inseparable regions, thus describing the same part (object). The CRSs are determined by a region boundary graph (RBG) which is defined as a graph whose nodes represent regions, and the edges represent boundaries: convex and concave. Since jump boundaries represent no physical contact in 3-D, they are represented as null edges. A CRS is defined as a set of regions (or nodes in an RBG) such that for each pair of regions in the set, there is a path, which is represented only by convex edges. The physical interpretation is that a CRS represents part of an object such that the regions in the set cannot be separated.< >

关键词： Image segmentation Image analysis Testing Military computing Robots Laboratories Image recognition Solid modeling Optimization methods Labeling

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Computational themes in applications of visual perception

Computational themes in applications of visual perception

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AIAA/NASA/USAF 2nd Symposium on Automation, robotics and Advanced Computing for the National Space Program,1987

作者： Jain, Ramesh Schunck, Brian G. Weymouth, Terry Computer Vision Research Laboratory Department of Electrical Engineering and Computer Science University of Michigan Ann ArborMI48109-2122 United States

The paper summarizes the current research in the computer vision research laboratory at the University of Michigan. The laboratory concentrates on developing generic vision algorithms for industrial applications. Generic vision algorithms can be applied to a wide variety of inspection problems. The paper includes a discussion of the current state of the machine vision industry and provides recommendations for improving the transfer of vision technology from research to practice. according to applications areas. There are no automotive vision algorithms or aerospace vision algorithms;vision algorithms are not specific to any one industry. vision algorithms are defined by the properties of the vision processing task;that is, in terms that depend on the vision processing itself, rather than on some intended use for the algorithm. © 1987 by the American Institute of Aeronautics and Astronautics, Inc.

关键词： computer vision

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TOWARD EFFICIENT TRAJECTORY PLANNING - THE PATH-VELOCITY DECOMPOSITION

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INTERNATIONAL JOURNAL OF robotics research 1986年第3期5卷 72-89页

作者： KANT, K ZUCKER, SW Computer Vision and Robotics Laboratory Department of Electrical Engineering McGill University Montréal Québec Canada H3A2A7

We present a novel approach to solving the trajectory planning problem (TPP) in time-varying environments. The essence of our approach lies in a heuristic but natural decomposition of TPP into two subproblems: (1) planning a path to avoid collision with static obstacles and (2) planning the velocity along the path to avoid collision with moving obstacles. We call the first subproblem the path planning problem (PPP) and the second the velocity planning problem (VPP). Thus, our decomposition is summarized by the equation TPP right arrow PPP + VPP. The symbol right arrow indicates that the decomposition holds under certain assumptions, e.g., when obstacles are moving independently of (i.e., not tracking) the robot. Furthermore, we pose the VPP in path-time space, where time is explicitly represented as an extra dimension, and reduce it to a graph search in this space. In fact, VPP is transformed to a two-dimensional PPP in path-time space with some additional constraints. Algorithms are then presented to solve the VPP with different optimality criteria: minimum length in path-time space, and minimum time. [ABSTRACT FROM AUTHOR]

关键词： robotics

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