If you have ever hiked up a steep hill to reach a viewpoint, you will know that sensing can involve the expenditure of effort. More generally, the choice of which movement an intelligent system chooses to make is usually based on information gleaned from sensors. But the information required to make the motion decision may not be immediately to hand, so the system . first has to plan a motion whose purpose is to acquire the needed sensor information. Again, this conforms to our everyday experience: I am in the woods and don't know which direction to go, so I climb up to the ridge to get my bearings; I am lost in a new town, so I plan to drive to the next junction where there is sure to be a roadsign, failing that I will ask someone who seems to be from the locality. Why, if experiences such as these are so familiar, has the problem only recently been recognised and studied in Robotics? One reason is that until quite recently Robotics research was dominated by work on robot arms with limited reach and fixed in a workcell.

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Authors and Affiliations

University of Pennsylvania, USA

Gregory D. Hager

Bibliographic Information

Book Title: Task-Directed Sensor Fusion and Planning
Book Subtitle: A Computational Approach
Authors: Gregory D. Hager
Series Title: The Springer International Series in Engineering and Computer Science
DOI: https://doi.org/10.1007/978-1-4613-1545-2
Publisher: Springer New York, NY
eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 1990
Hardcover ISBN: 978-0-7923-9108-1Published: 31 May 1990
Softcover ISBN: 978-1-4612-8828-2Published: 23 May 2013
eBook ISBN: 978-1-4613-1545-2Published: 06 December 2012
Series ISSN: 0893-3405
Edition Number: 1
Number of Pages: XVIII, 254
Topics: Control, Robotics, Mechatronics, Computer Imaging, Vision, Pattern Recognition and Graphics, Artificial Intelligence

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Table of contents (9 chapters)

Front Matter

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