In: 2022 30th Mediterranean Conference on Control and Automation (MED). Mediterranean Conference on Control and Automation (MED), Pages 604-611, IEEE, 6/2022.
Zusammenfassung
Operation of robotic manipulators is limited to structured environments and well-defined tasks due to an offline path planning. However, flexible production processes and human-robot collaboration necessitates a real time path planning to allow for replanning a path in changing environments. In this work, we investigate established planning algorithms for their applicability to dynamic path planning problems. We further compare these methods with our approach based on model predictive control. We consider a single manipulator with six degrees of freedom in static and dynamic environments. We investigate three experimental setups and show the advantages of the proposed MPC-ELS approach over more traditional path planning algorithms in terms of several metrics, such as path-length, execution time or trajectory smoothness. In addition, we propose a scheduling algorithm for object allocation to determine an optimal sequence for pick and place tasks with regard to minimum execution time.
@inproceedings{pub12911,
author = {
Gafur, Nigora
and
Weber, Leo
and
Yfantis, Vassilios
and
Wagner, Achim
and
Ruskwoski, Martin
},
title = {Dynamic path planning and reactive scheduling for a robotic manipulator using nonlinear model predictive control},
booktitle = {2022 30th Mediterranean Conference on Control and Automation (MED). Mediterranean Conference on Control and Automation (MED)},
year = {2022},
month = {6},
pages = {604--611},
publisher = {IEEE}
}
Deutsches Forschungszentrum für Künstliche Intelligenz German Research Center for Artificial Intelligence