Using Many-Sorted Logic in the Object-Oriented Data Model for Fast Robot Task Planning

Authors:
Y. P. Chien;Anand Hudli;Mathew Palakal
Affiliations:
Department of Electrical Engineering, Purdue University, School of Engineering and Technology at Indianapolis, 723 W. Michigan Street, Indianapolis, IN 46202, USA;Department of Computer and Information Science, Purdue University, School of Science at Indianapolis, 723 W. Michigan Street, Indianapolis, IN 46202, USA;Department of Computer and Information Science, Purdue University, School of Science at Indianapolis, 723 W. Michigan Street, Indianapolis, IN 46202, USA
Venue:
Journal of Intelligent and Robotic Systems
Year:
1998

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Abstract

Search space explosion is a critical problem in robot task planning. Thisproblem limits current robot task planners to solve only simple block worldproblems and task planning in a real robot working environment to beimpractical. This problem is mainly due to the lack of utilization of domaininformation in task planning. In this paper, we describe a fast task plannerfor indoor robot applications that effectively uses domain information tospeed up the planning process. In this planner, domain information isexplicitly represented in an object-oriented data model (OODM) that usesmany-sorted logic (MSL) representation. The OODM is convenient for themanagement of complex data and many-sorted logic is effective for pruning inthe rule search process. An inference engine is designed to take advantageof the salient features of these two techniques for fast task planning. Asimulation example and complexity analysis are given to demonstrate theadvantage of the proposed task planner.