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Hybrid conditional planning using answer set programming

Published online by Cambridge University Press:  22 August 2017

IBRAHIM FARUK YALCINER ,
AHMED NOUMAN ,
VOLKAN PATOGLU  and
ESRA ERDEM Open the ORCID record for ESRA ERDEM [Opens in a new window]
IBRAHIM FARUK YALCINER
Affiliation:
Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey (e-mail: [email protected], [email protected], [email protected], [email protected])
AHMED NOUMAN
Affiliation:
Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey (e-mail: [email protected], [email protected], [email protected], [email protected])
VOLKAN PATOGLU
Affiliation:
Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey (e-mail: [email protected], [email protected], [email protected], [email protected])
ESRA ERDEM
Affiliation:
Faculty of Engineering and Natural Sciences, Sabanci University, Istanbul, Turkey (e-mail: [email protected], [email protected], [email protected], [email protected])
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Abstract

We introduce a parallel offline algorithm for computing hybrid conditional plans, called HCP-ASP, oriented towards robotics applications. HCP-ASP relies on modeling actuation actions and sensing actions in an expressive nonmonotonic language of answer set programming (ASP), and computation of the branches of a conditional plan in parallel using an ASP solver. In particular, thanks to external atoms, continuous feasibility checks (like collision checks) are embedded into formal representations of actuation actions and sensing actions in ASP; and thus each branch of a hybrid conditional plan describes a feasible execution of actions to reach their goals. Utilizing nonmonotonic constructs and nondeterministic choices, partial knowledge about states and nondeterministic effects of sensing actions can be explicitly formalized in ASP; and thus each branch of a conditional plan can be computed by an ASP solver without necessitating a conformant planner and an ordering of sensing actions in advance. We apply our method in a service robotics domain and report experimental evaluations. Furthermore, we present performance comparisons with other compilation based conditional planners on standardized benchmark domains.

Keywords

Conditional planninghybrid planninganswer set programmingcognitive robotics
Type
Regular Papers
Information
Theory and Practice of Logic Programming , Volume 17 , Special Issue 5-6: 33rd International Conference on Logic Programming , September 2017 , pp. 1027 - 1047
Copyright
Copyright © Cambridge University Press 2017 

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