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Learning the inverse kinematics of a robot manipulator using the Bees Algorithm

Pham, D. T., Castellani, M. and Fahmy, Ashraf 2008. Learning the inverse kinematics of a robot manipulator using the Bees Algorithm. Presented at: 6th IEEE International Conference on Industrial Informatics, Daejeon, South Korea, 13-16 July 2008. Industrial Informatics, 2008. INDIN 2008. 6th IEEE International Conference on. IEEE, pp. 493-498. 10.1109/INDIN.2008.4618151

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Abstract

In this paper, the Bees algorithm was used to train multi-layer perceptron neural networks to model the inverse kinematics of an articulated robot manipulator arm. The Bees Algorithm is a recently developed parameter optimisation algorithm that is inspired by the foraging behaviour of honey bees. The Bees Algorithm performs a kind of exploitative neighbourhood search combined with random explorative search. Three neural networks were trained to reproduce a set of input/output numerical examples of the inverse kinematics of the main three joints of an articulated robotic manipulator. The results prove the remarkable robustness of the Bees Algorithm, which consistently trained the neural networks to model the kinematics data with very high accuracy. The learning results obtained by the proposed algorithm are compared to the results obtained by the standard Backpropagation Algorithm and an Evolutionary Algorithm. The comparative study highlights the superior performance of the proposed Bees Algorithm over the other algorithms.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Centre for Advanced Manufacturing Systems At Cardiff (CAMSAC)
Engineering
Subjects: T Technology > TK Electrical engineering. Electronics Nuclear engineering
Publisher: IEEE
ISBN: 9781424421701
Last Modified: 29 Apr 2016 03:46
URI: http://orca.cf.ac.uk/id/eprint/69256

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