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Mobile Robot Planning using Action Language
BC
with Hierarchical Domain Abstractions (2014)
Shiqi Zhang
, Fangkai Yang,
Piyush Khandelwal
, and
Peter Stone
Action language
BC
provides an elegant way of formalizing robotic domains which need to be expressed using default logic as well as indirect and recursive action effects. However, generating plans efficiently for large domains using
BC
can be challenging, even when state-of-the-art answer set solvers are used. In this paper, we investigate the computational gains achieved by describing task planning domains at different abstraction levels using
BC
, where lower levels describe more domain details by adding fluents not included in higher levels and actions at different levels are formalized independently. Two algorithms are presented to efficiently calculate the near-optimal short and low-cost plans respectively. We present a case study where at least an order of magnitude speedup was achieved in a robot mail collection task using hierarchical domain abstractions.
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Citation:
In
The 7th Workshop on Answer Set Programming and Other Computing Paradigms (ASPOCP)
, July 2014.
Bibtex:
@inproceedings{ASPOCP14-zhang, title={Mobile Robot Planning using Action Language
BC
with Hierarchical Domain Abstractions}, author={Shiqi Zhang and Fangkai Yang and Piyush Khandelwal and Peter Stone}, booktitle={The 7th Workshop on Answer Set Programming and Other Computing Paradigms (ASPOCP)}, month={July}, url="http://www.cs.utexas.edu/users/ai-lab?zhang:aspocp14", year={2014} }
People
Piyush Khandelwal
Ph.D. Alumni
piyushk [at] cs utexas edu
Peter Stone
Faculty
pstone [at] cs utexas edu
Shiqi Zhang
Postdoctoral Alumni
szhang [at] cs utexas edu
Areas of Interest
Action Languages
Planning
Robotics
Labs
Learning Agents