Path-Following Control with Path and Orientation Snap-In
Christian Hartl-Nesic, Elias Pritzi, Andreas Kugi
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.
BibTeX
@inproceedings{iros2023_pathfollowingcon,
title = {Path-Following Control with Path and Orientation Snap-In},
author = {Christian Hartl-Nesic and Elias Pritzi and Andreas Kugi},
booktitle = {IROS 2023},
year = {2023}
}