首页 | 本学科首页   官方微博 | 高级检索  
     


Reaching a goal with directional uncertainty
Authors:Mark de Berg   Leonidas Guibas   Dan Halperin   Mark Overmars   Otfried Schwarzkopf   Micha Sharir  Monique Teillaud
Affiliation:

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

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 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 from where we can reach infinity with a directional uncertainty of . We prove that the maximum complexity of is O(n/5). 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 . For both situations we also prove lower bounds on the maximum complexity, and we give efficient algorithms for computing the regions.

Keywords:
本文献已被 ScienceDirect 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号