We present a new scheme for the adaptive control of mechanical manipulators along with proof of convergence. This work is an extension of our earlier work [Craig, Hsu and Sastry] [1]. The new scheme does not require t...
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We present a new scheme for the adaptive control of mechanical manipulators along with proof of convergence. This work is an extension of our earlier work [Craig, Hsu and Sastry] [1]. The new scheme does not require the measurement of joint accelerations and needs less computation. We illustrate the theory with some simulations.
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) pla...
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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]
This paper explains a simple method for fast collision detection in manipulator tasks. We show from examples taken in the literature that solutions to this problem can be chosen among a continuum of schemes, according...
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This paper explains a simple method for fast collision detection in manipulator tasks. We show from examples taken in the literature that solutions to this problem can be chosen among a continuum of schemes, according to the method selected for representing the workspace and the robot, and the amount of computations performed before testing a particular trajectory. We then describe a method based on a recursive decomposition of the workspace, also referred to as an octree model, as a good tradeoff for a class of applications.
Adaptive control has been recognized as an effective approach for mechanical robot manipulator controller design due to the presence of nonlinearties and uncertainties in robot dynamic models. Numerous results address...
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Adaptive control has been recognized as an effective approach for mechanical robot manipulator controller design due to the presence of nonlinearties and uncertainties in robot dynamic models. Numerous results addressing different aspects of the control problem have been reported in the literature in recent years. The purpose of this paper is to present an indepth review of these existing developments whereby the robot adaptive control problems and solutions are systematically studied. The essential overall objective is to unify the various design ideas under a common frame work. Within this frame work, the various design techniques are catagorized into three groups; (i) model-reference adaptive control, (ii) Self tuning adaptive control, and (iii) Linear perturbation adaptive control. The design conditions and solutions of each technique are discussed, and the relationships between these techniques are examined. Finally some remarks on the effectiveness and implementation of adaptive controllers are presented.
A common task in computervision is to recognize the objects in an image. Most computervision systems do this by matching models for each possible object type in turn, recognizing objects by the best matches. This is...
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A common task in computervision is to recognize the objects in an image. Most computervision systems do this by matching models for each possible object type in turn, recognizing objects by the best matches. This is not ideal, as it does not take advantage of the similarities and differences between the possible object types. The computation time also increases linearly with the number of possible objects, which can become a problem if the number is large. This paper describes a new recognition method, the feature indexed hypotheses method, which takes advantage of the similarities and differences between object types, and is able to handle cases, where there are a large number of possible object types, in sub-linear computation time. A two-dimensional occluded parts recognition system using this method is described.
Vertical integration of transformation of abstract assembly task descriptions into task execution commands is needed to overcome the fundamental factors which limit the widespread application of current robotic system...
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Vertical integration of transformation of abstract assembly task descriptions into task execution commands is needed to overcome the fundamental factors which limit the widespread application of current robotic systems. These factors are the requirements for precise control of the robot task environment, custom-designed fixtures and end-effectors, and on-site robot control programming. These requirements arise because current robotic systems do not have an understanding of the robot cell environment. Further, these systems are not able to react rationally to non-deterministic events which occur during task execution. A research plan which is aimed at the systematic incorporation of limited amounts of machine intelligence into robot task planning and execution is outlined.
This paper describes a system that applies vision techniques to extract acoustic patterns in the speech spectrogram. By processing a spectrographic image through a set of edge detectors and combining their outputs, th...
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This paper describes a system that applies vision techniques to extract acoustic patterns in the speech spectrogram. By processing a spectrographic image through a set of edge detectors and combining their outputs, the system obtains two-dimensional objects that characterize the formant patterns and general spectral properties for vowels and consonants. As a validation of the approach, a limited vowel recognition experiment was performed on the "object" spectrograms. Preliminary results show that this processing technique retains relevant acoustic information necessary to identify the underlying phonetic representation.
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 pointill...
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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 second for 2-dimensional flows (or Type II processes). We conjecture that this difference is reflected in the response properties of “simple” and “complex” cells, respectively, and predict several other psychophysical phenomena.
The problem of simplifying the Lagrange dynamic equation of PUMA 600 robot manipulators is considered. By applying the numeric significance evaluation procedure to the symbolically expressed dynamic projection functio...
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The Ada research Group of the roboticsresearchlaboratory at The University of Michigan is currently developing a real-time distributed computing capability based upon the premises that real-time distributed language...
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