Abstract
Designing a reconfigurable manufacturing robotic workcell is a complex and resource demanding procedure. In this work a multi criteria index is introduced, allowing the designer to evaluate the various anatomies achieved by a reconfigurable manipulator, and to define the area in the manipulator’s configuration space where a task can be accomplished with good performance under the selected performance measure. An adaptive neuro-fuzzy inference system is trained, in order to rapidly produce the index value for arbitrary anatomies achieved by the manipulator. The system is tested using a case study reconfigurable manipulator, and the derived results determined by the system after its training are presented and compared to the actual index value for calculated for the relevant anatomy.
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Valsamos, H., Moulianitis, V., Aspragathos, N. (2010). Rapid Evaluation of Reconfigurable Robots Anatomies Using Computational Intelligence. In: Setchi, R., Jordanov, I., Howlett, R.J., Jain, L.C. (eds) Knowledge-Based and Intelligent Information and Engineering Systems. KES 2010. Lecture Notes in Computer Science(), vol 6277. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15390-7_35
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DOI: https://doi.org/10.1007/978-3-642-15390-7_35
Publisher Name: Springer, Berlin, Heidelberg
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