학술논문

The sensor selection problem for bounded uncertainty sensing models
Document Type
Conference
Source
IPSN 2005. Fourth International Symposium on Information Processing in Sensor Networks, 2005. Microelectronics and electron devices Information Processing in Sensor Networks, 2005. IPSN 2005. Fourth International Symposium on. :151-158 2005
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Signal Processing and Analysis
Components, Circuits, Devices and Systems
Uncertainty
Robot sensing systems
Estimation error
State estimation
Probability distribution
Information technology
Computer errors
Cameras
Approximation algorithms
Mobile robots
Language
Abstract
We address the problem of selecting sensors so as to minimize the error in estimating the position of a target. We consider a generic sensor model where the measurements can be interpreted as polygonal, convex subsets of the plane. This model applies to a large class of sensors including cameras. We present an approximation algorithm which guarantees that the resulting error in estimation is within a factor 2 of the least possible error. In establishing this result, we formally prove that a constant number of sensors suffice for a good estimate-an observation made by many researchers. In the second part of the paper, we study the scenario where the target's position is given by an uncertainty region and present algorithms for both probabilistic and online versions of this problem.