Interleaving Planning and Execution for Autonomous Robots / Edition 1

by Illah Reza Nourbakhsh

Overview

Interleaving Planning and Execution for Autonomous Robots develops a formal representation for interleaving planning and execution in the context of incomplete information. This work bridges the gap between theory and practice in robotics by presenting control architectures that are provably sound, complete and optimal, and then describing real-world implementations of these robot architectures. Dervish, winner of the 1994 AAAI National Robot Contest, is one of the robots featured.
Interleaving Planning and Execution for Autonomous Robots is based on the author's PhD research, covering the same material taught in CS 224, the very popular Introduction to Robot Programming Laboratory taught at Stanford for four years by Professor Michael Genesereth and the author.

Product Details

ISBN-13:	9780792398288
Publisher:	Springer US
Publication date:	11/30/1996
Series:	The Springer International Series in Engineering and Computer Science , #385
Edition description:	1997
Pages:	145
Product dimensions:	6.10(w) x 9.25(h) x 0.02(d)

Table of Contents

1 Introduction.- 1.1 Motivation.- 1.2 Contributions.- 1.3 Contents of Chapters.- 2 Perception and Action.- 2.1 The Situated Robot and its Environment.- 2.2 Defining State and State Update.- 2.3 Comparison to other Conventional Approaches.- 2.4 Conclusion.- 3 Formalizing Incomplete Information.- 3.1 Sources of Incomplete Information.- 3.2 Representing Incomplete Information.- 3.3 State-Set Tracking: Execution Monitoring.- 3.4 Related Work.- 4 Goal-Directed Control Systems.- 4.1 Defining a Problem Instance.- 4.2 Advance Planning Control Systems.- 4.3 Related Work.- 5 Interleaving Planning and Execution.- 5.1 Introduction: Interleaving.- 5.2 Premature Search Termination.- 5.3 Experimental Results.- 5.4 Related Work.- 6 Using Assumptions to Oversimplify.- 6.1 Introduction.- 6.2 Assumptions.- 6.3 Assumptive Control Systems.- 6.4 Continuous Selection Algorithm.- 6.5 The Cost of Assumptions.- 6.6 Large-scale Real-World Experimental Results.- 6.7 Related Work.- 6.8 Conclusion.- 7 Strategic Subgoaling: Using Abstraction Systems.- 7.1 Introduction.- 7.2 Problem Spaces.- 7.3 Abstraction.- 7.4 Examples of Abstraction Systems and their Cost.- 7.5 Related Work and Discussion.- 8 Generalizing beyond State Sets.- 8.1 Introduction.- 8.2 Representation Examples.- 8.3 Conclusion.- 9 Conclusions.

Editorial Reviews

Covers the same material as the graduate and undergraduate course Robot Programming Laboratory that Nourbadksh co-taught at Stanford University. Develops a formal representation for interleaving planning and execution in the context of incomplete information. Bridges the gap between theory and practice in robotics by presenting control architectures that are able to be proven sound, complete, and optimal; and by describing real-world implementations of the robot architectures. Annotation c. by Book News, Inc., Portland, Or.

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