Evolutionary Algorithms Techniques Based on MET Heuristics of Accustomed Computing Performance
DOI:
https://doi.org/10.51983/ajcst-2017.6.1.1776Keywords:
Biogeography based Optimization-Aisle planning-Obstacle detection-Robotic ManipulatorAbstract
In robotics manipulators, the aisle should be optimum, appropriately the torque of the apprentice can be minimized in adjustment to save power. This cardboard includes an optimal aisle planning arrangement for a automatic manipulator. Recently, techniques based on metaheuristics of accustomed computing, mainly evolutionary algorithms (EA), accept been auspiciously activated to a ample amount of automatic applications. In this cardboard the bigger BBO algorithm is acclimated to abbreviate the cold action in the attendance of altered obstacles. The simulation represents that the proposed optimal aisle planning adjustment has satisfactory performance.
References
M. Abbaszadeh and H. J. Marquez, "Nonlinear observer design for one-sided Lipschitz systems," in American Control Conference (ACC), 2010, pp. 5284-5289.
A. Nearchou and N. Aspragathos, "Collision-free continuous path control of manipulators using genetic algorithms," Journal of Systems Engineering, vol. 6, pp. 20-32, 1996.
M. Chen and A. M. Zalzala, "A genetic approach to the motion planning of redundant mobile manipulator systems considering safety and configuration," 1995.
E. S. Pires and J. Machado, "A GA perspective of the energy requirements for manipulators maneuvering in a workspace with obstacles," in Evolutionary Computation, 2000. Proceedings of the 2000 Congress on, 2000, pp. 1110-1116.
S. Yue, D. Henrich, W. Xu, and S. Tso, "Point-to-point trajectory planning of flexible redundant robot manipulators using genetic algorithms," Robotica, vol. 20, pp. 269-280, 2002.
E. S. Pires, J. T. Machado, and P. M. Oliveira, "An evolutionary approach to robot structure and trajectory optimization," in Transactions of the 10th IEEE Conference on Advanced Robotics, 2001, pp. 333-338.
L. Tian and C. Collins, "An effective robot trajectory planning method using a genetic algorithm," Mechatronics, vol. 14, pp. 455-470, 2004.
D. Chwa, J. Kang, and J. Y. Choi, "Online trajectory planning of robot arms for interception of fast maneuvering object under torque and velocity constraints," Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on, vol. 35, pp. 831-843, 2005.
D. Simon, "Biogeography-based optimization," Evolutionary Computation, IEEE Transactions on, vol. 12, pp. 702-713, 2008.
A. Ghavifekr, S. Ghaemi, and R. Behinfaraz, "A Modified Biogeography Based Optimization (BBO) Algorithm for Time Optimal Motion Planning of 5 DOF PC-based Gryphon Robot."
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2017 The Research Publication
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
