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Design and VLSI implementation of pe...

Sun, Yu.

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Design and VLSI implementation of perceptive controller for robotic systems.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Design and VLSI implementation of perceptive controller for robotic systems./
作者:	Sun, Yu.
面頁冊數:	125 p.
附註:	Source: Dissertation Abstracts International, Volume: 65-12, Section: B, page: 6569.
Contained By:	Dissertation Abstracts International65-12B.
標題:	Engineering, Electronics and Electrical. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3159010
ISBN:	0496917862

Design and VLSI implementation of perceptive controller for robotic systems.
Sun, Yu.

Design and VLSI implementation of perceptive controller for robotic systems. - 125 p.

Source: Dissertation Abstracts International, Volume: 65-12, Section: B, page: 6569.

Thesis (Ph.D.)--Michigan State University, 2004.

Intuitively, human intelligence largely depends on the perception from interaction with the environment and the object. Similarly, robotic systems can sense the dynamic changes of the environment and the object states during the task execution. This dissertation is aimed at developing approaches for modeling, analyzing and designing robotic control systems based on the robotic perception, i.e., a perceptive frame.

ISBN: 0496917862Subjects--Topical Terms:

626636
Engineering, Electronics and Electrical.

Design and VLSI implementation of perceptive controller for robotic systems.
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245 1 0 $a Design and VLSI implementation of perceptive controller for robotic systems.
300 $a 125 p.
500 $a Source: Dissertation Abstracts International, Volume: 65-12, Section: B, page: 6569.
500 $a Adviser: Ning Xi.
502 $a Thesis (Ph.D.)--Michigan State University, 2004.
520 $a Intuitively, human intelligence largely depends on the perception from interaction with the environment and the object. Similarly, robotic systems can sense the dynamic changes of the environment and the object states during the task execution. This dissertation is aimed at developing approaches for modeling, analyzing and designing robotic control systems based on the robotic perception, i.e., a perceptive frame.
520 $a In the perceptive frame, the model of a task can be learned by the robot based on the perception. In this dissertation, a model identification method for unknown parameters of a nonholonomic cart has been developed. Using interactions between a mobile manipulator and the cart, sensory information is accrued to estimate the model parameters of the cart. Since the raw data is contaminated by noise that cannot be modeled statistically, a wavelet based Least Square Method (LSM) is proposed to estimate these parameters for the cart. Experimental results verify that the estimation accuracy can be significantly improved by the use of the proposed lease square method.
520 $a For the control issues in the perceptive frame, an perceptive hybrid system approach for the motion planning and control of mobile robot systems is proposed. The ability to deal with unexpected events is one of the essential aspects of robot intelligence. Robotic systems can respond to environmental information obtained from sensors by making task decisions. According to the task decisions, the system is able to modify the original planned path and control the robot to execute the task autonomously. Perceptive model with single perceptive reference can deal with unexpected events only at the continuous level. It allows the perceptive reference to be blocked and resumed by a class of unexpected events, including obstacles. The perceptive hybrid system model has three layers, one continuous layer, two discrete layers. Corresponding to the three layers, one continuous perceptive reference and two discrete perceptive references. The discrete layers enable the robot system to make decisions and modify original path plans. The properties of the system model, including linearity, continuity, stability in switching, and some dynamical properties of unexpected events have been discussed in the hybrid linguistic framework. The evolution of the hybrid perceptive references cannot be stopped by blocking the continuous perceptive reference. The properties have been verified by experiments. (Abstract shortened by UMI.)
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