Data-Based Stiffness Estimation for Control of Robot–Workpiece Elastic Interactions

Abstract

Abstract In manufacturing operations such as clamping and drilling of elastic structures, tool–workpiece normality must be maintained, and shear forces minimized to avoid tool or workpiece damage. The challenge is that the combined stiffness of a robot and workpiece, needed to control the robot–workpiece elastic interactions, are often difficult to model and can vary due to geometry changes of the workpiece caused by large deformations and associated pose variations of the robot. The main contribution of this article is an algorithm (i) to learn the robot–workpiece stiffness relationship using a model-free data-based approach and (ii) to use it for applying desired forces and torques on the elastic structure. Moreover, comparative experiments with and without the data-based stiffness estimation show that clamping operating speed is increased by four times when using the stiffness estimation method while interaction forces and torques are kept within acceptable bounds.