A Meta-Heuristic Paradigm for solving the Forward Kinematics of 6-6 General Parallel Manipulator

Date

2009-12-18

Author

Chandra, Rohitash
Frean, Marcus
Rolland, Luc

Metadata

Show full item record

This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Item Usage Stats

86
views

0
downloads

The forward kinematics of the general Gough platform, namely the 6-6 parallel manipulator is solved using hybrid meta-heuristic techniques in which the simulated annealing algorithm replaces the mutation operator in a genetic algorithm. The results are compared with the standard simulated annealing and genetic algorithm. It shows that the standard simulated annealing algorithm outperforms standard genetic algorithm in terms of computation time and overall accuracy of the solution on this problem. However, the hybrid meta-heuristic paradigm shows the best performance in terms of accuracy and success rate.

Subject Keywords

Neural-network, Tabu-search, Optimization, Algorithms, Performance

URI

https://hdl.handle.net/11511/66922

Collections

Department of Computer Engineering, Conference / Seminar

Suggestions

OpenMETU
Core

Solving the Forward Kinematics of the 3RPR Planar Parallel Manipulator using a Hybrid Meta-Heuristic Paradigm Chandra, Rohitash; Zhang, Mengjie; Rolland, Luc (2009-12-18) The forward kinematic of the 3-RPR parallel manipulator is solved using a hybrid meta-heuristic technique where the simulated annealing algorithm replaces the mutation operator in a genetic algorithm. The results from the hybrid meta-heuristic approach is compared with the standard simulated annealing and genetic algorithm. The results show that the simulated annealing algorithm outperforms genetic algorithm in terms of computation time and overall accuracy of the solution. The hybrid meta-heuristic search ...
A parallel ant colony optimization algorithm based on crossover operation Kalınlı, Adem; Sarıkoç, Fatih (Springer, 2018-11-01) In this work, we introduce a new parallel ant colony optimization algorithm based on an ant metaphor and the crossover operator from genetic algorithms.The performance of the proposed model is evaluated usingwell-known numerical test problems and then it is applied to train recurrent neural networks to identify linear and nonlinear dynamic plants. The simulation results are compared with results using other algorithms.
A neuro-fuzzy MAR algorithm for temporal rule-based systems Sisman, NA; Alpaslan, Ferda Nur; Akman, V (1999-08-04) This paper introduces a new neuro-fuzzy model for constructing a knowledge base of temporal fuzzy rules obtained by the Multivariate Autoregressive (MAR) algorithm. The model described contains two main parts, one for fuzzy-rule extraction and one for the storage of extracted rules. The fuzzy rules are obtained from time series data using the MAR algorithm. Time-series analysis basically deals with tabular data. It interprets the data obtained for making inferences about future behavior of the variables. Fu...
A neural network method for direction of arrival estimation with uniform circular dipole array in the presence of mutual coupling Caylar, Selcuk; Leblebicioğlu, Mehmet Kemal; Dural, Guelbin (2007-06-16) In recent years application of Neural Network (NN) algorithms in both target tracking problem and DoA estimation have become popular because of the increased computational efficiency This paper presents the implementation of modified neural network algorithm(MN-MUST) to the uniform circular dipole array in the presence of mutual coupling. In smart antenna systems, mutual coupling between elements can significantly degrade the processing algorithms. In this paper mutual coupling affects on MN-MUST has been i...
An interactive preference based multiobjective evolutionary algorithm for the clustering problem Demirtaş, Kerem; Özdemirel, Nur Evin; Karasakal, Esra; Department of Industrial Engineering (2011) We propose an interactive preference-based evolutionary algorithm for the clustering problem. The problem is highly combinatorial and referred to as NP-Hard in the literature. The goal of the problem is putting similar items in the same cluster and dissimilar items into different clusters according to a certain similarity measure, while maintaining some internal objectives such as compactness, connectivity or spatial separation. However, using one of these objectives is often not sufficient to detect differ...

Citation Formats

R. Chandra, M. Frean, and L. Rolland, “A Meta-Heuristic Paradigm for solving the Forward Kinematics of 6-6 General Parallel Manipulator,” 2009, p. 171, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/66922.