Sensorless and adaptive admittance control of industrial robot in physical human−robot interaction
•A sensorless and adaptive admittance control of an industrial robot is proposed for physical human−robot interaction.•A comprehensive dynamic model of the industrial robot is obtained to enable the external force detection.•The dynamics of robot in the process of mode switching is explored and comp...
Gespeichert in:
Veröffentlicht in: | Robotics and computer-integrated manufacturing 2018-06, Vol.51, p.158-168 |
---|---|
Hauptverfasser: | , , , , , |
Format: | Artikel |
Sprache: | eng |
Schlagworte: | |
Online-Zugang: | Volltext |
Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
Zusammenfassung: | •A sensorless and adaptive admittance control of an industrial robot is proposed for physical human−robot interaction.•A comprehensive dynamic model of the industrial robot is obtained to enable the external force detection.•The dynamics of robot in the process of mode switching is explored and compensated effectively.•RBF network is used to tune the admittance controller online to make human−robot interaction more natural and easier.
As industrial robots are applied in manufacturing industry on a large-scale and human intelligence is regarded as an important part in manufacturing, physical human−robot interaction (pHRI) which integrates the strength and accuracy of robot with human operator's ability of task cognition has drawn the attention of both academia and industry. However, an industrial robot without extra force/torque sensor for interacting force monitoring cannot be used directly in pHRI, and research on pHRI of industrial robots remains a challenge. In this research, a comprehensive dynamic model of an industrial robot in both dynamic mode and quasi-static mode is obtained to calculate the external force produced by human operator in pHRI and enables sensorless pHRI for industrial robots even in the environment with ambient vibration. Particularly, the dynamics in the process of mode switching which has not been investigated by researchers is studied and compensated by an empirical but effective method. Admittance control is used to transfer the detected force into reference position and velocity of the robot. RBF (Radial Basis Function) network is used to update the damping parameter online in order to reduce the contact force change and the contact force which makes pHRI more natural and easier. The stability of the controller is also discussed. The proposed methods of external force detection and adaptive admittance control show satisfactory behaviour in the experiments. |
---|---|
ISSN: | 0736-5845 1879-2537 1879-2537 |
DOI: | 10.1016/j.rcim.2017.12.004 |