Data Association with Ambiguous Measurements - Robotics Institute Carnegie Mellon University

Data Association with Ambiguous Measurements

M. Travers, T. Murphey, and L. Pao
Conference Paper, Proceedings of American Control Conference (ACC '08), pp. 1875 - 1880, June, 2008

Abstract

We address the problem of tracking a single object in the neighborhood of several other closely spaced, similar objects where the sensor used to do the tracking may randomly measure the wrong object. Unlike many tracking scenarios, there is no other environmental clutter producing additional erroneous measurements. The objects move together, and the sensor provides one measurement at every time step, either due to the object of interest or due to one of the other similar nearby objects. This situation of having a "mixed" set of measurements of unknown origin occurs in real world systems. While we consider the mixed-measurement problem in an example scenario, the algorithms developed can be applied to any number of associated systems with little alteration.

BibTeX

@conference{Travers-2008-107843,
author = {M. Travers and T. Murphey and L. Pao},
title = {Data Association with Ambiguous Measurements},
booktitle = {Proceedings of American Control Conference (ACC '08)},
year = {2008},
month = {June},
pages = {1875 - 1880},
}
Copyright notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. These works may not be reposted without the explicit permission of the copyright holder.