Using Knowledge Representation and Task Planning for Robot-agnostic Skills on the Example of Contact-Rich Wiping Tasks
Mayr, Matthias LU
; Ahmad, Faseeh
LU
; Duerr, Alexander
LU
and Krueger, Volker
LU
(2023)
19th IEEE International Conference on Automation Science and Engineering, CASE 2023
In IEEE International Conference on Automation Science and Engineering
2023-August.
- Abstract
The transition to agile manufacturing, Industry 4.0, and high-mix-low-volume tasks require robot programming solutions that are flexible. However, most deployed robot solutions are still statically programmed and use stiff position control, which limit their usefulness. In this paper, we show how a single robot skill that utilizes knowledge representation, task planning, and automatic selection of skill implementations based on the input parameters can be executed in different contexts. We demonstrate how the skill-based control platform enables this with contact-rich wiping tasks on different robot systems. To achieve that in this case study, our approach needs to address different kinematics, gripper types, vendors, and fundamentally... (More)
The transition to agile manufacturing, Industry 4.0, and high-mix-low-volume tasks require robot programming solutions that are flexible. However, most deployed robot solutions are still statically programmed and use stiff position control, which limit their usefulness. In this paper, we show how a single robot skill that utilizes knowledge representation, task planning, and automatic selection of skill implementations based on the input parameters can be executed in different contexts. We demonstrate how the skill-based control platform enables this with contact-rich wiping tasks on different robot systems. To achieve that in this case study, our approach needs to address different kinematics, gripper types, vendors, and fundamentally different control interfaces. We conducted the experiments with a mobile platform that has a Universal Robots UR5e 6 degree-of-freedom robot arm with position control and a 7 degree-of-freedom KUKA iiwa with torque control.
(Less)
- author
- Mayr, Matthias
LU
; Ahmad, Faseeh
LU
; Duerr, Alexander
LU
and Krueger, Volker
LU
- organization
- publishing date
- 2023
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Robotics, Knowledge Representation, Task Planning
- host publication
- 2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023
- series title
- IEEE International Conference on Automation Science and Engineering
- volume
- 2023-August
- publisher
- IEEE - Institute of Electrical and Electronics Engineers Inc.
- conference name
- 19th IEEE International Conference on Automation Science and Engineering, CASE 2023
- conference location
- Auckland, New Zealand
- conference dates
- 2023-08-26 - 2023-08-30
- external identifiers
-
- scopus:85174401915
- ISSN
- 2161-8089
- 2161-8070
- ISBN
- 9798350320695
- DOI
- 10.1109/CASE56687.2023.10260413
- project
- SkiRoS: Skills for Robotic Systems for enabling agile production
- Reinforcement Learning in Continuous Spaces with Interactively Acquired Knowledge-based Models
- SkiRoS: Skills for Robotic Systems for enabling agile production
- WASP Professor Package: Cognitive Robots for Manufacturing
- RobotLab LTH
- Efficient Learning of Robot Skills
- Robotics and Semantic Systems
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © 2023 IEEE.
- id
- afb3d358-fe52-40ca-8130-e8bfc27af8ba
- alternative location
- https://arxiv.org/abs/2308.14206
- date added to LUP
- 2023-12-20 13:58:43
- date last changed
- 2024-04-18 23:37:57
@inproceedings{afb3d358-fe52-40ca-8130-e8bfc27af8ba,
abstract = {{<p>The transition to agile manufacturing, Industry 4.0, and high-mix-low-volume tasks require robot programming solutions that are flexible. However, most deployed robot solutions are still statically programmed and use stiff position control, which limit their usefulness. In this paper, we show how a single robot skill that utilizes knowledge representation, task planning, and automatic selection of skill implementations based on the input parameters can be executed in different contexts. We demonstrate how the skill-based control platform enables this with contact-rich wiping tasks on different robot systems. To achieve that in this case study, our approach needs to address different kinematics, gripper types, vendors, and fundamentally different control interfaces. We conducted the experiments with a mobile platform that has a Universal Robots UR5e 6 degree-of-freedom robot arm with position control and a 7 degree-of-freedom KUKA iiwa with torque control.</p>}},
author = {{Mayr, Matthias and Ahmad, Faseeh and Duerr, Alexander and Krueger, Volker}},
booktitle = {{2023 IEEE 19th International Conference on Automation Science and Engineering, CASE 2023}},
isbn = {{9798350320695}},
issn = {{2161-8089}},
keywords = {{Robotics; Knowledge Representation; Task Planning}},
language = {{eng}},
publisher = {{IEEE - Institute of Electrical and Electronics Engineers Inc.}},
series = {{IEEE International Conference on Automation Science and Engineering}},
title = {{Using Knowledge Representation and Task Planning for Robot-agnostic Skills on the Example of Contact-Rich Wiping Tasks}},
url = {{http://dx.doi.org/10.1109/CASE56687.2023.10260413}},
doi = {{10.1109/CASE56687.2023.10260413}},
volume = {{2023-August}},
year = {{2023}},
}