Manipulator Redundancy Reduction as a Tool for Reinforcing Motion Planning Using Genetic Algorithms

Javadi, Amir-Homayoun (2008) Manipulator Redundancy Reduction as a Tool for Reinforcing Motion Planning Using Genetic Algorithms. In: Proceedings of the World Congress on Engineering 2008 Vol II WCE. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Abstract

A novel approach to plan an optimum motion of redundant robot manipulators for a predefined end-effector trajectory using genetic algorithms (GA) is presented. The efficiency of the proposed approach, without loss of generality, is demonstrated through a simulation carried out on a planar 6-DOF robot manipulator. The approach benefits from two key features. First, the method of data representation which guarantees the satisfaction of joints angle limits, and second the conversion of considered model’s 6-DOF construction to 4-DOF construction along with an additional binary value which guarantees the exact placement of the end-effector on the predefined trajectory. Comparison with three other approaches shows that the result of the presented solution is substantially better. In addition the difference of two kinds of Random Number Generator (RNG) is addressed. It is shown that using RNG with normal distribution leads to faster convergence of the proposed algorithm than RNG with uniform distribution.

Item Type: Conference or workshop item (Lecture)
Uncontrolled keywords: Genetic Algorithms,Manipulator,Motion Planning,Trajectory Tracking
Subjects: T Technology > TJ Mechanical engineering and machinery > Control engineering
Divisions: Faculties > Sciences > School of Engineering and Digital Arts > Instrumentation, Control and Embedded Systems
Depositing User: Amir-Homayoun Javadi
Date Deposited: 03 Dec 2015 11:35 UTC
Last Modified: 29 May 2019 16:34 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/52612 (The current URI for this page, for reference purposes)
Javadi, Amir-Homayoun: https://orcid.org/0000-0003-0569-6441
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