TY - JOUR
T1 - Optimum design of parallelogram five-bar manipulator for dexterous workspace by using ELEMAEF in differential evolution
AU - Villarreal-Cervantes, Miguel G.
AU - De la Cruz-Muciño, Daniel
AU - Portilla-Flores, Edgar A.
PY - 2014/9
Y1 - 2014/9
N2 - The kinematic design of mechanism is an important stage in the design methodology. A dexterous workspace for a manipulator is an outstanding characteristic that must be considered in it. Hence, a mono-objective constraint optimization problem (MOCOP) for the kinematic design of a manipulator with three revolute joints (3R robot), that fulfils a defined dexterous workspace, is formulated. The MOCOP is solved by proposing a mechanism in the differential evolution (DE) algorithm called exhaustive local exploitation mechanism with adaptive scale factor (ELEMAEF). This mechanism exhaustively exploits a local region in the search space with the information of the base and the difference vectors of good trial vector, in an attempt to generate better individuals in the same direction. In addition, the ELEMAEF guides the evolution of the population toward a better zone without sacrificing the search capabilities of the DE algorithm. A comparison of the DE algorithm with and without the ELEMAEF for this particular design problem is presented. The use of the ELEMAEF gives a superior performance in the DE algorithm.
AB - The kinematic design of mechanism is an important stage in the design methodology. A dexterous workspace for a manipulator is an outstanding characteristic that must be considered in it. Hence, a mono-objective constraint optimization problem (MOCOP) for the kinematic design of a manipulator with three revolute joints (3R robot), that fulfils a defined dexterous workspace, is formulated. The MOCOP is solved by proposing a mechanism in the differential evolution (DE) algorithm called exhaustive local exploitation mechanism with adaptive scale factor (ELEMAEF). This mechanism exhaustively exploits a local region in the search space with the information of the base and the difference vectors of good trial vector, in an attempt to generate better individuals in the same direction. In addition, the ELEMAEF guides the evolution of the population toward a better zone without sacrificing the search capabilities of the DE algorithm. A comparison of the DE algorithm with and without the ELEMAEF for this particular design problem is presented. The use of the ELEMAEF gives a superior performance in the DE algorithm.
KW - Dexterous manipulator
KW - Differential evolution
KW - Evolutionary algorithm
KW - Kinematic design
KW - Parallelogram manipulator
UR - http://www.scopus.com/inward/record.url?scp=84896815392&partnerID=8YFLogxK
U2 - 10.12785/amis/080506
DO - 10.12785/amis/080506
M3 - Artículo
SN - 1935-0090
VL - 8
SP - 2129
EP - 2140
JO - Applied Mathematics and Information Sciences
JF - Applied Mathematics and Information Sciences
IS - 5
ER -