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Introduction to AI Robotics

Murphy, R.R.·2001·Industrial Robot: An International Journal

Abstract

From the Publisher: This text covers all the material needed to understand the principles behind the AI approach to robotics and to program an artificially intelligent robot for applications involving sensing, navigation, planning, and uncertainty. Robin Murphy is extremely effective at combining theoretical and practical rigor with a light narrative touch. In the overview, for example, she touches upon anthropomorphic robots from classic films and science fiction stories before delving into the nuts and bolts of organizing intelligence in robots. Following the overview, Murphy contrasts AI and engineering approaches and discusses what she calls the three paradigms of AI robotics: hierarchical, reactive, and hybrid deliberative/reactive. Later chapters explore multiagent scenarios, navigation and path-planning for mobile robots, and the basics of computer vision and range sensing. Each chapter includes objectives, review questions, and exercises. Many chapters contain one or more case studies showing how the concepts were implemented on real robots. Murphy, who is well known for her classroom teaching, conveys the intellectual adventure of mastering complex theoretical and technical material.

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Metadata

Authors
Murphy, R. R.
Venue
Industrial Robot: An International Journal
Publisher
Emerald
Published
2001-06-01
Volume
28
Issue
3
Pages
266-267
ISSN
0143-991X (ISSN-L)
OpenAlex
W2250706791
Cited by
1,052
References
0
FWCI
82.73
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Introduction to AI Robotics. https://app.cochat.ai/papers/10.1108/ir.2001.28.3.266.1
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Murphy, R. R. (2001). Introduction to AI Robotics. Industrial Robot: An International Journal. https://doi.org/10.1108/ir.2001.28.3.266.1

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.