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Amir Feizollahi
Rene V. Mayorga



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Amir Feizollahi
Rene V. Mayorga


WSEAS Transactions on Systems and Control


Print ISSN: 1991-8763
E-ISSN: 2224-2856

Volume 12, 2017

Notice: As of 2014 and for the forthcoming years, the publication frequency/periodicity of WSEAS Journals is adapted to the 'continuously updated' model. What this means is that instead of being separated into issues, new papers will be added on a continuous basis, allowing a more regular flow and shorter publication times. The papers will appear in reverse order, therefore the most recent one will be on top.


Volume 12, 2017


On the Modeling and the Optimal Motion Planning of Manipulators via a Modified D* Lite Search Algorithm

AUTHORS: Amir Feizollahi, Rene V. Mayorga

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ABSTRACT: The motion planning of the manipulators is a topic in robotics that has been studied extensively and there are many solutions available in the literature. However, the motion planning of manipulators considering the system dynamics with respect to their energy consumption level is still a challenging problem which requires a combination of interdisciplinary studies to yield an optimal solution. In this paper, a framework is developed to model the user-defined manipulator, design a motion planner implementing a proposed search algorithm, and simulate the robot motion in different environments. The superiority of the search algorithm is investigated and the development of the MATLAB framework is discussed thoroughly accompanying the simulation results. Key-Words: - Manipulator dynamics, Motion planning, Trajectory optimization, Graph search

KEYWORDS: Manipulator dynamics, Motion planning, Trajectory optimization, Graph search


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[10] A. Feizollahi and R. V. Mayorga, “Optimized Motion Planning of Manipulators in PartiallyKnown Environment Using Modified D* Lite Algorithm”, WSEAS Transactions on Systems, vol. 16, no. 10, pp. 69-75, 2017.

[11] A. Feizollahi. “Collison Free and Energetically Optimized Motion Planning of Manipulators in Partially Known Environment Using Modified D* Lite Algorithm;” M.A.Sc. Dissertation Faculty of Graduate Studies and Research, University of Regina, 2016.

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[13] Y. Lu, X. Huo, O. Arslan, and P. Tsiotras, “Incremental Multi-Scale Search Algorithm for Dynamic Path Planning With Low Worst-Case Complexity,” IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics) vol. 41, no.6, pp. 1556–1570, 2011.

WSEAS Transactions on Systems and Control, ISSN / E-ISSN: 1991-8763 / 2224-2856, Volume 12, 2017, Art. #15, pp. 148-157


Copyright © 2017 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0

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