ScienceDirect® Home Skip Main Navigation Links
You have guest access to ScienceDirect. Find out more.
 
Home
Browse
My Settings
Alerts
Help
 Quick Search
 Search tips (Opens new window)
    Clear all fields    
advertisementadvertisement
Theoretical Computer Science
Volume 140, Issue 2, 3 April 1995, Pages 301-317
Design and Analysis of Geometrical Algorithms for Robot Motion Planning and Vision
 
Font Size: Decrease Font Size  Increase Font Size
 Abstract - selected
Purchase PDF (1239 K)

 
 
 
Related Articles in ScienceDirect
View More Related Articles
 
View Record in Scopus
 
doi:10.1016/0304-3975(94)00237-D    How to Cite or Link Using DOI (Opens New Window)
Copyright © 1995 Published by Elsevier Science B.V.

Reaching a goal with directional uncertainty*1

Mark de Berga, Corresponding Author Contact Information, E-mail The Corresponding Author, Leonidas Guibasb, Dan Halperinb, Mark Overmarsa, Otfried Schwarzkopfa, Micha Sharird, c and Monique Teillaude

a Vakgroep Informatica, Universiteit Utrecht, Postbus 80.089, 3508, TB Utrecht, Netherlands b Department of Computer Science, Stanford University, Stanford, CA 94305-2095, USA c School of Mathematical Sciences, Tel Aviv University, Ramat-Aviv 69978, Israel d Courant Institute of Mathematical Sciences, New York University, 251 Mercer Street, New York, NY 10012-1185, USA e INRIA, B.P. 93, 06902, Sophia-Antipolis Cedex, France

Available online 22 December 1999.

Purchase the full-text article



References and further reading may be available for this article. To view references and further reading you must purchase this article.

Abstract

We study two problems related to planar motion planning for robots with imperfect control, where, if the robot starts a linear movement in a certain commanded direction, we only know that its actual movement will be confined in a cone of angle α centered around the specified direction.

First, we consider a single goal region, namely the “region at infinity”, and a set of polygonal obstacles, modeled as a set S of n line segments. We are interested in the region Image from where we can reach infinity with a directional uncertainty of α. We prove that the maximum complexity of Image is O(n5). Second, we consider a collection of k polygonal goal regions of total complexity m, but without any obstacles. Here we prove an O(k3m) bound on the complexity of the region from where we can reach a goal region with a directional uncertainty of α. For both situations we also prove lower bounds on the maximum complexity, and we give efficient algorithms for computing the regions.

Article Outline

• References

Theoretical Computer Science
Volume 140, Issue 2, 3 April 1995, Pages 301-317
Design and Analysis of Geometrical Algorithms for Robot Motion Planning and Vision
 
Home
Browse
My Settings
Alerts
Help
Elsevier.com (Opens new window)
About ScienceDirect  |  Contact Us  |  Information for Advertisers  |  Terms & Conditions  |  Privacy Policy
Copyright © 2008 Elsevier B.V. All rights reserved. ScienceDirect® is a registered trademark of Elsevier B.V.