Abstract
Robots need to be as simple to use as tools in a workshop and allow non-experts to program, modify and execute tasks. In particular for repetitive tasks in high-mix/low-volume production, robotic support and physical human-robot interaction (pHRI) help to significantly increase productivity. In path-following control (PFC), the geometric description of the path is decoupled from the time evolution of the robot's end-effector along the path. PFC is inherently suitable for pHRI since path progress can be derived from the interaction with the human. In this work, an extension to multi-path PFC is proposed, which allows smooth transitions between the paths initiated by the human. Additionally, two pHRI modes called path snap-in and orientation snap-in are proposed, which use attractive forces to snap the robot end-effector onto a path or a predefined orientation. Moreover, the stability properties of PFC are inherited and the method is applicable to linear, nonlinear and self-intersecting paths. The proposed pHRI modes are validated on an experimental drilling task for teach-in (using orientation snap-in) and execution (using path snap-in) with the kinematically redundant collaborative robot Kuka Lbr iiwa 14 R820.
| Originalsprache | Englisch |
|---|---|
| Titel | Proceedings of 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
| DOIs | |
| Publikationsstatus | Veröffentlicht - Okt. 2023 |
| Veranstaltung | 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) - Detroit, USA/Vereinigte Staaten Dauer: 1 Okt. 2023 → 5 Okt. 2023 |
Konferenz
| Konferenz | 2023 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) |
|---|---|
| Land/Gebiet | USA/Vereinigte Staaten |
| Stadt | Detroit |
| Zeitraum | 1/10/23 → 5/10/23 |
Research Field
- Complex Dynamical Systems