by Armin Müller, Alexandra Kirsch and Michael Beetz
Abstract:
We propose an approach to transformational planning and learning of everyday activity. This approach is targeted at autonomous robots that are to perform complex activities such as household chore. Our approach operates on flexible and reliable plans suited for long-term activity and applies plan transformations that generate competent and high-performance robot behavior. We show as a proof of concept that general transformation rules can be formulated that achieve substantially and significantly improved performance using table setting as an example.
Reference:
Armin Müller, Alexandra Kirsch and Michael Beetz, "Transformational Planning for Everyday Activity", In Proceedings of the 17th International Conference on Automated Planning and Scheduling (ICAPS'07), Providence, USA, pp. 248–255, 2007.
Bibtex Entry:
@InProceedings{mueller07transformational,
author = {Armin M{\"u}ller and Alexandra Kirsch and Michael Beetz},
title = {Transformational Planning for Everyday Activity},
booktitle = {Proceedings of the 17th International Conference on Automated Planning and Scheduling (ICAPS'07)},
year = {2007},
month = {September},
address = {Providence, USA},
pages = {248--255},
bib2html_pubtype = {Conference Paper},
bib2html_rescat = {Planning},
bib2html_groups = {Cogito},
abstract = { We propose an approach to transformational planning and learning of
everyday activity. This approach is targeted at autonomous robots
that are to perform complex activities such as household chore. Our
approach operates on flexible and reliable plans suited for
long-term activity and applies plan transformations that generate
competent and high-performance robot behavior. We show as a proof
of concept that general transformation rules can be formulated that
achieve substantially and significantly improved performance using
table setting as an example. }}