Evolutionary bi-criteria optimum design of robots based on task specifications View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2009-03

AUTHORS

R. Saravanan, S. Ramabalan, N. Godwin Raja Ebenezer, R. Natarajan

ABSTRACT

The optimum robot structure design problem based on task specifications is an important one, since it has greater influence on manipulator workspace design, vibrations of the manipulator during operation, manipulator efficiency in the work environment and power consumption. In this paper, an optimization robot structure problem is formulated with the objective of determining the optimal geometric dimensions of the robot manipulators considering the task specifications (pick and place operation). The aim is to minimize torque required for motion and maximize manipulability measure of the robot subject to dynamic, kinematic, deflection and structural constraints with link physical characteristics (length and cross-sectional area parameters) as design variables. In this work, five different cross-sections (hollow circle, hollow square, hollow rectangle, C-channel and I-channel) have been experimented for the link. Three evolutionary optimization algorithms namely multi-objective genetic algorithm (MOGA), elitist nondominated sorting genetic algorithm (NSGA-II) and multi-objective differential evolution (MODE) are used for the optimum structural design of 2-link and 3-link planar robots. Two methods (normalized weighting objective functions and average fitness factor) are used to select the best optimal solution. Two multiobjective performance measures namely solution spread measure and ratio of non-dominated individuals are used to evaluate the Pareto optimal fronts. Two more multiobjective performance measures namely optimiser overhead and algorithm effort, are used to find computational effort of optimization algorithm. The results obtained from various techniques are compared and analyzed. More... »

PAGES

386-406

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00170-008-1483-8

DOI

http://dx.doi.org/10.1007/s00170-008-1483-8

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1014429787


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