Hard material small-batch industrial machining robot
•Laser-profiler-based sensor modules for part localisation to be machined.•Fast and easy-to-use calibration procedure for calibrating freely locatable force sensors.•New offline path compensation method based on robot stiffness and machining models.•Motor-closed-loop-position controls (Extended Elas...
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Veröffentlicht in: | Robotics and computer-integrated manufacturing 2018-12, Vol.54, p.185-199 |
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Hauptverfasser: | , , , , , , , , , , |
Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Laser-profiler-based sensor modules for part localisation to be machined.•Fast and easy-to-use calibration procedure for calibrating freely locatable force sensors.•New offline path compensation method based on robot stiffness and machining models.•Motor-closed-loop-position controls (Extended Elastic Joints –EEJ– model) and torque-ripple compensation (TRC).•Intuitive and efficient robot-programming environment for non-skilled operators based on visual programming.
Hard materials can be cost effectively machined with standard industrial robots by enhancing current state-of-the-art technologies. It is demonstrated that even hard metals with specific robotics-optimised novel hard-metal tools can be machined by standard industrial robots with an improved position-control approach and enhanced compliance-control functions. It also shows that the novel strategies to compensate for elastic robot errors, based on models and advanced control, as well as the utilisation of new affordable sensors and human-machine interfaces, can considerably improve the robot performance and applicability of robots in machining tasks. In conjunction with the development of safe robots for human-robot collaboration and cooperation, the results of this paper provide a solid background for establishing industrial robots for industrial-machining applications in both small- and medium-size enterprises and large industry. The planned short-term and long-term exploitation of the results should significantly increase the future robot usage in the machining operations. |
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ISSN: | 0736-5845 1879-2537 |
DOI: | 10.1016/j.rcim.2017.11.004 |