Human-robot collaborative object transfer using human motion prediction based on Cartesian pose Dynamic Movement Primitives
(2021) p.3758-3764- Abstract
- In this work, the problem of human-robot collaborative object transfer to unknown target poses is addressed. The desired pattern of the end-effector pose trajectory to a known target pose is encoded using DMPs (Dynamic Movement Primitives). During transportation of the object to new unknown targets, a DMP-based reference model and an EKF (Extended Kalman Filter) for estimating the target pose and time duration of the human's intended motion is proposed. A stability analysis of the overall scheme is provided. Experiments using a Kuka LWR4+ robot equipped with an ATI sensor at its end-effector validate its efficacy with respect to the required human effort and compare it with an admittance control scheme.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/63aa8a72-557f-4413-bb62-92905799c5c2
- author
- Sidiropoulos, Antonis ; Karayiannidis, Yiannis LU and Doulgeri, Zoe
- publishing date
- 2021
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- 2021 IEEE International Conference on Robotics and Automation (ICRA)
- pages
- 7 pages
- external identifiers
-
- scopus:85123922002
- DOI
- 10.1109/ICRA48506.2021.9562035
- language
- English
- LU publication?
- no
- id
- 63aa8a72-557f-4413-bb62-92905799c5c2
- date added to LUP
- 2022-12-14 15:08:27
- date last changed
- 2024-01-29 22:56:34
@inproceedings{63aa8a72-557f-4413-bb62-92905799c5c2, abstract = {{In this work, the problem of human-robot collaborative object transfer to unknown target poses is addressed. The desired pattern of the end-effector pose trajectory to a known target pose is encoded using DMPs (Dynamic Movement Primitives). During transportation of the object to new unknown targets, a DMP-based reference model and an EKF (Extended Kalman Filter) for estimating the target pose and time duration of the human's intended motion is proposed. A stability analysis of the overall scheme is provided. Experiments using a Kuka LWR4+ robot equipped with an ATI sensor at its end-effector validate its efficacy with respect to the required human effort and compare it with an admittance control scheme.}}, author = {{Sidiropoulos, Antonis and Karayiannidis, Yiannis and Doulgeri, Zoe}}, booktitle = {{2021 IEEE International Conference on Robotics and Automation (ICRA)}}, language = {{eng}}, pages = {{3758--3764}}, title = {{Human-robot collaborative object transfer using human motion prediction based on Cartesian pose Dynamic Movement Primitives}}, url = {{http://dx.doi.org/10.1109/ICRA48506.2021.9562035}}, doi = {{10.1109/ICRA48506.2021.9562035}}, year = {{2021}}, }