NDLI: Using Constrained Intuitionistic Linear Logic for Hybrid Robotic Planning Problems

Content Provider	IEEE Xplore Digital Library
Author	Saranli, U. Pfenning, F.
Copyright Year	2007
Description	Author affiliation: Dept. of Comput. Eng., Bilkent Univ., Ankara (Saranli, U.)
Abstract	Synthesis of robot behaviors towards nontrivial goals often requires reasoning about both discrete and continuous aspects of the underlying domain. Existing approaches in building automated tools for such synthesis problems attempt to augment methods from either discrete planning or continuous control with hybrid elements, but largely fail to ensure a uniform treatment of both aspects of the domain. In this paper, we present a new formalism, constrained intuitionistic linear logic (CILL), merging continuous constraint solvers with linear logic to yield a single language in which hybrid properties of robotic behaviors can be expressed and reasoned with. Following a gentle introduction to linear logic, we describe the two new connectives of CILL, introduced to interface the constraint domain with the logical fragment of the language. We then illustrate the application of CILL for robotic planning problems within the balanced blocks world, a "physically realistic" extension of the blocks world domain. Even though some of the formal proofs for the semantic foundations of the language as well as an efficient implementation of a theorem prover are yet to be completed, CILL promises to be a powerful formalism in reasoning within hybrid domains.
Sponsorship	IEEE Robotics and Automation Soc
Starting Page	3705
Ending Page	3710
File Size	155449
Page Count	6
File Format	PDF
ISBN	1424406013
ISSN	10504729
DOI	10.1109/ROBOT.2007.364046
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-04-10
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robotics and automation Constraint theory Logic programming Automatic control Merging Intelligent robots Artificial intelligence Control theory Mathematics Scalability
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Control and Systems Engineering Electrical and Electronic Engineering Software

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