We present a new model for the perceptual reasoning involved in hand/eye coordination, and we show how this model can be developed into a control mechanism for a robot manipulator with a visual sensor. This new approa...
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The medial axis transform (MAT) is a sparse representation of shape, which, being reversible, has potential for binary image compression. The MAT also provides structural information not accessible with alternative bi...
The authors present a systematic comparison of three commonly used least-squares based methods that describes the relationship between noise levels, patch sizes and reliability of surface classification in computer vi...
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The authors present a systematic comparison of three commonly used least-squares based methods that describes the relationship between noise levels, patch sizes and reliability of surface classification in computervision. The different methods were tested on several sets of synthetic and real data. Complete sets of quadric surfaces were tested. In each case the standard deviation of the Gaussian noise ranged from 0 to 0.05. Four different patch sizes were tested in each case representing data from the entire surface, half surface, quarter surface and from a small patch of the surface. Similar tests were made for two different types of real range data, a sphere and a cylinder. Both synthetic and real data showed improvement in the results obtained by using the M-estimate method in the case of gross outlying points.< >
We present a model for flexible extruded objects, such as wires, tubes, or grommets, and demonstrate a novel, *** seven-dimensional Hough transform that derives and analyzes their three-space curved axes from position...
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The problem of efficient path planning for a point robot in a partially known dynamic environment is considered. The static known part of the environment consists of point shelters distributed in planar terrain, and t...
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The problem of efficient path planning for a point robot in a partially known dynamic environment is considered. The static known part of the environment consists of point shelters distributed in planar terrain, and the dynamic, unknown part is abstracted in the form of alarms that cause the robot to leave its current (pre-planned) path and divert to the nearest shelter. A probabilistic analysis of the expected times for the dynamic paths generated when the alarms follow a Poisson distribution with parameter lambda is given. A case study with three shelters serves to illustrate the dependence of the expected travel times on lambda for two alternate static paths. Two different strategies are presented for the general case of n shelters and shown to be superior for different ranges of values of the alarm rate lambda (very low and very high values, respectively).< >
The authors present a general framework for reasoning about robotic manipulation tasks involving a moving target, where manipulation is loosely defined to include catching, hitting, interception, etc. This framework m...
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The authors present a general framework for reasoning about robotic manipulation tasks involving a moving target, where manipulation is loosely defined to include catching, hitting, interception, etc. This framework may be used to achieve robust vision-based control. The different levels at which visual input is involved in pursuing the dynamically defined goal are considered. A given task is first transformed into one of constrained trajectory planning on a topological space defined by a set of image parameters. A learning phase first learns the qualitative features of this perceptual control surface so that further operations may be carried out autonomously without precise calibration of different parts of the system. The framework facilitates the incorporation of learning strategies to automate the control mechanism.< >
The author addresses the problem of visual navigation, and through it the more general problem of sensor-mediated movement. A new approach to the navigation problem is proposed, in which visual processes are closely a...
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The author addresses the problem of visual navigation, and through it the more general problem of sensor-mediated movement. A new approach to the navigation problem is proposed, in which visual processes are closely and actively integrated with the control of the robotic system. In the case of obstacle avoidance, the concepts of free space doors and corridors are introduced and it is shown that this dynamic information is easier to extract from the sequence of incoming images than the depth map traditionally used. Though poorer in content, the information is still sufficient for the purpose of closed-loop planning and control of trajectories to the goal.< >
An approach to hand/eye coordination that does not require any calibration and hence overcomes some of the shortcomings of traditional approaches is presented. It is demonstrated how the concepts of the perceptual kin...
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An approach to hand/eye coordination that does not require any calibration and hence overcomes some of the shortcomings of traditional approaches is presented. It is demonstrated how the concepts of the perceptual kinematic map and control surface of the hand/eye system allow the modeling and solution of the grasping problem. The close integration of visual information with the decision process and reliance on qualitative, topological information rather than on the exact values of the maps allow robust visual control of the robot manipulator. The principles of the approach are general, and the algorithm and system presented here represent only one of many possible ways to implement and test the approach.< >
作者:
J. AloimonosComputer Vision Laboratory
Center for Automation Research Institute for Advanced Computer Studies Computer Science Department University of Maryland College Park MD USA
Qualitative vision, which in the past has been wrongly called inexact, makes sense when it is coupled with purposive vision, which formulates questions for which qualitative solutions are possible. To demonstrate the ...
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Qualitative vision, which in the past has been wrongly called inexact, makes sense when it is coupled with purposive vision, which formulates questions for which qualitative solutions are possible. To demonstrate the usefulness of this approach, the author considers visual motion (or navigation) problems, and assumes that the observer is active. He describes the preliminary design of Medusa, a purposive and qualitative visual motion machine that can robustly solve many navigational problems without reconstructing the scene.< >
The authors performed several experiments where they made sure that the only cues available to the observer were contour and motion. It turns out that when humans combine information from contour and motion to reconst...
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The authors performed several experiments where they made sure that the only cues available to the observer were contour and motion. It turns out that when humans combine information from contour and motion to reconstruct the shape of an object in view, if the results of the two modules-shape from contour and structure from motion-are inconsistent, they totally discard one of the cues and an illusion is experienced. The authors describe examples of such illusions and identify the conditions under which they happen. Finally, they introduce a computational theory for combining contour and motion using the theory of regularization. The theory explains such illusions and predicts many more.< >
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