Elasto-geometrical modeling and calibration of robot manipulators: Application to machining and forming applications

• Robots' pose accuracy improvement with an elasto-geometrical calibration method
• Parametric modeling & fuzzy inference system to achieve elastic modeling
• Identification of the elasto-geometrical models with experimental data
• Discussion about each elastic model, on the task and user requirement topics
• Validation of the fuzzy logic elastic model through an experimental forming process

This paper proposes an original elasto-geometrical calibration method to improve the static pose accuracy of industrial robots involved in machining, forming or assembly applications. Two approaches are presented respectively based on an analytical parametric modeling and a Takagi–Sugeno fuzzy inference system. These are described and then discussed. This allows to list the main drawbacks and advantages of each of them with respect to the task and the user requirements. The fuzzy logic model is used in a model-based compensation scheme to increase significantly the robot static pose accuracy in a context of incremental forming application. Experimental results show the efficiency of the fuzzy logic model while minimizing development and computational resources.