Application of genetic algorithms to point-to-point motion of redundant manipulators

In this paper, the problem of point-to-point motion of redundant robot manipulators working in environments with obstacles is considered. The problem is formulated as a constrained optimization problem and is solved using a method based on genetic algorithms (GAs). The objetive of this method is to...

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Bibliographic Details
Published inMechanism and machine theory Vol. 31; no. 3; pp. 261 - 270
Main Authors Nearchou, A.C., Aspragathos, N.A.
Format Journal Article
LanguageEnglish
Published Oxford Elsevier Ltd 01.04.1996
New York, NY Elsevier
Subjects
Applied sciences
Drives
Exact sciences and technology
Linkage mechanisms, cams
Mechanical engineering. Machine design
Positioning
Planar mechanism
Redundancy
Kinematics
Theoretical study
Manipulators
Collision avoidance
Robotics
Genetic algorithms
Constrained optimization
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Summary:In this paper, the problem of point-to-point motion of redundant robot manipulators working in environments with obstacles is considered. The problem is formulated as a constrained optimization problem and is solved using a method based on genetic algorithms (GAs). The objetive of this method is to minimize the end-effector's positional error subject to the obstacle avoidance constraints. The efficiency of the proposed method is demonstrated through multiple experiments carried out on a redundant planar manipulator.
ISSN:0094-114X
1873-3999
DOI:10.1016/0094-114X(95)00074-9