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Object-oriented Model-based Extensions of Robot Control Languages (bibtex)
Object-oriented Model-based Extensions of Robot Control Languages (bibtex)
by A Müller, A Kirsch and M Beetz
Abstract:
More than a decade after mobile robots arrived in many research labs it is still difficult to find plan-based autonomous robot controllers that perform, beyond doubt, better than they possibly could without applying AI methods. One of the main reason for this situation is abstraction. AI based control techniques typically abstract away from the mechanisms that generate the physical behavior and refuse the use of control structures that have proven to be necessary for producing flexible and reliable robot behavior. The consequence is: AI-based control mechanisms can neither explain and diagnose how a certain behavior resulted from a given plan nor can they revise the plans to improve its physical performance. In our view, a substantial improvement on this situation is not possible without having a new generation of robot control languages. These languages must, on the one hand, be expressive enough for specifying and producing high performance robot behavior and, on the other hand, be transparent and explicit enough to enable execution time inference mechanisms to reason about, and manipulate these control programs. This paper reports on aspects of the design of RPL-II, which we propose as such a next generation control language. We describe the nuts and bolts of extending our existing language R P L to support explicit models of physical systems, and object-oriented modeling of control tasks and programs. We show the application of these concepts in the context of autonomous robot soccer.
Reference:
Object-oriented Model-based Extensions of Robot Control Languages (A Müller, A Kirsch and M Beetz), In 27th German Conference on Artificial Intelligence, 2004. 
Bibtex Entry:
@inproceedings{Mue04Obj,
 author = {A Müller and A Kirsch and M Beetz},
 title = {Object-oriented Model-based Extensions of Robot Control Languages},
 booktitle = {27th German Conference on Artificial Intelligence},
 year = {2004},
 bib2html_pubtype = {Conference Paper},
 bib2html_rescat = {Planning,Action},
 bib2html_groups = {AGILO,Cogito},
 bib2html_funding = {AGILO},
 bib2html_keywords = {Robot, Language, Representation},
 abstract = {More than a decade after mobile robots arrived in many research labs it is still difficult to find
              plan-based autonomous robot controllers that perform, beyond doubt, better than they possibly could
              without applying AI methods. One of the main reason for this situation is abstraction. AI based
              control techniques typically abstract away from the mechanisms that generate the physical behavior
              and refuse the use of control structures that have proven to be necessary for producing flexible
              and reliable robot behavior. The consequence is: AI-based control mechanisms can neither explain
              and diagnose how a certain behavior resulted from a given plan nor can they revise the plans to
              improve its physical performance. In our view, a substantial improvement on this situation is not
              possible without having a new generation of robot control languages. These languages must, on the
              one hand, be expressive enough for specifying and producing high performance robot behavior and, on
              the other hand, be transparent and explicit enough to enable execution time inference mechanisms to
              reason about, and manipulate these control programs. This paper reports on aspects of the design of
              RPL-II, which we propose as such a next generation control language. We describe the nuts and bolts
              of extending our existing language R P L to support explicit models of physical systems, and
              object-oriented modeling of control tasks and programs. We show the application of these concepts
              in the context of autonomous robot soccer.},
}
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