Mobile Robot Planning using Action Language BC with Hierarchical Domain Abstractions (2014)
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.
In The 7th Workshop on Answer Set Programming and Other Computing Paradigms (ASPOCP), July 2014.

Piyush Khandelwal Ph.D. Alumni piyushk [at] cs utexas edu
Peter Stone Faculty pstone [at] cs utexas edu
Fangkai Yang Ph.D. Alumni fkyang [at] cs utexas edu
Shiqi Zhang Postdoctoral Alumni szhang [at] cs utexas edu