Editors:
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Computer Science (LNCS, volume 2554)
Part of the book sub series: Lecture Notes in Artificial Intelligence (LNAI)
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Table of contents (7 chapters)
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Front Matter
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Back Matter
About this book
Robotic agents, such as autonomous office couriers or robot tourguides, must be both reliable and efficient. Thus, they have to flexibly interleave their tasks, exploit opportunities, quickly plan their course of action, and, if necessary, revise their intended activities.
This book makes three major contributions to improving the capabilities of robotic agents:
- first, a plan representation method is introduced which allows for specifying flexible and reliable behavior
- second, probabilistic hybrid action models are presented as a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans
- third, the system XFRMLEARN capable of learning structured symbolic navigation plans is described in detail.
Editors and Affiliations
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Institut für Informatik IX, Technische Universität München, Garching b. München
Michael Beetz
Bibliographic Information
Book Title: Plan-Based Control of Robotic Agents
Book Subtitle: Improving the Capabilities of Autonomous Robots
Editors: Michael Beetz
Series Title: Lecture Notes in Computer Science
DOI: https://doi.org/10.1007/3-540-36381-5
Publisher: Springer Berlin, Heidelberg
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eBook Packages: Springer Book Archive
Copyright Information: Springer-Verlag Berlin Heidelberg 2002
Softcover ISBN: 978-3-540-00335-9Published: 13 December 2002
eBook ISBN: 978-3-540-36381-1Published: 01 July 2003
Series ISSN: 0302-9743
Series E-ISSN: 1611-3349
Edition Number: 1
Number of Pages: XI, 194
Topics: Robotics and Automation, Artificial Intelligence, Computer Science, general, Computer Communication Networks, Special Purpose and Application-Based Systems, Control, Robotics, Mechatronics