Robotic manipulators with double encoders: accuracy improvement based on advanced stiffness modeling and intelligent control

The paper deals with advanced stiffness modeling and intelligent control of industrial robots with double encoders. In contrast to previous works that concentrate on the actuator compliance compensation, this work is aimed at reduction of the compliance errors produced by all manipulator components. Particular attention is paid to the identifiability of the stiffness model parameters using a combination of the tool location measurements and information from double encoders integrated into the actuated joints. For the considered architecture, new strategies for intelligent compliance error compensation are proposed. The developed techniques were applied to the stiffness modeling and accuracy improvement of a typical industrial robotic manipulator, for which the impact of external loading and gravity on the positioning accuracy was essentially reduced. (C) 2018, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.