Rapid evaluation of reconfigurable robots anatomies using computational intelligence

Authors:
Harry Valsamos;Vassilis Moulianitis;Nikos Aspragathos
Affiliations:
Mechanical and Aeronautics Engineering Dept., University of Patras, Rio, Achaia, Greece;Dept. of Product and Systems Design Engineering, University of Aegean, Syros, Greece;Mechanical and Aeronautics Engineering Dept., University of Patras, Rio, Achaia, Greece
Venue:
KES'10 Proceedings of the 14th international conference on Knowledge-based and intelligent information and engineering systems: Part II
Year:
2010

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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.