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Improving robotic machining accuracy through experimental error investigation and modular compensation

: Schneider, Ulrich; Drust, Manuel; Ansaloni, Matteo; Lehmann, Christian; Pellicciari, Marcello; Leali, Francesco; Gunnink, Jan Willem; Verl, Alexander


The International Journal of Advanced Manufacturing Technology 85 (2016), No.1, pp.3-15
ISSN: 0268-3768
ISSN: 1433-3015
European Commission EC
FP7; 25769; COMET
Journal Article
Fraunhofer IPA ()
robotics; machining; Fehlerkompensation; tracking; Fräsen; Fehleranalyse; Industrieroboter

Machining using industrial robots is currently limited to applications with low geometrical accuracies and soft materials. This paper analyzes the sources of errors in robotic machining and characterizes them in amplitude and frequency. Experiments under different conditions represent a typical set of industrial applications and allow a qualified evaluation. Based on this analysis, a modular approach is proposed to overcome these obstacles, applied both during program generation (offline) and execution (online). Predictive offline compensation of machining errors is achieved by means of an innovative programming system, based on kinematic and dynamic robot models. Real-time adaptive machining error compensation is also provided by sensing the real robot positions with an innovative tracking system and corrective feedback to both the robot and an additional high-dynamic compensation mechanism on piezo-actuator basis.