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Human-robot collaborative object transfer using human motion prediction based on Cartesian pose Dynamic Movement Primitives

Sidiropoulos, Antonis ; Karayiannidis, Yiannis LU orcid and Doulgeri, Zoe (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:
author
; and
publishing date
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}},
}