An official website of the United States government
Here’s how you know
Official websites use .gov
A .gov website belongs to an official government organization in the United States.
Secure .gov websites use HTTPS
A lock (
) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.
Quantifying Uncertainty Towards Information-Centric Unmanned Navigation
Published
Author(s)
Rajmohan (. Madhavan, Elena R. Messina
Abstract
Highly imperfect, inconsistent information and incomplete a priori knowledge introduce uncertainty in sensor-centric unmanned navigation systems. Understanding and quantifying uncertainty yields a measure of useful information that plays a critical role in several robotic navigation tasks such as sensor fusion, mapping, localization, path planning, and control. In this paper, within a probabilistic framework, we demonstrate the utility of estimation- and informationtheoretic concepts towards quantifying uncertainty using entropy and mutual information metrics in various contexts of unmanned navigation via experimental results.
Proceedings Title
Proceedings of the Performance Metrics for Intelligent Systems (PerMIS) Workshop
Conference Dates
August 16-18, 2003
Conference Location
Gaithersburg, MD, USA
Conference Title
Performance Metrics for Intelligent Systems (PerMIS) Workshop
Bayes Theorem, Entropy, Information Evaluation, LADAR., Sensor Uncertainty, Unmanned Navigation
Citation
Madhavan, R.
and Messina, E.
(2003),
Quantifying Uncertainty Towards Information-Centric Unmanned Navigation, Proceedings of the Performance Metrics for Intelligent Systems (PerMIS) Workshop, Gaithersburg, MD, USA, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=822569
(Accessed November 4, 2024)