Document Type
Article
Disciplines
Computer Engineering | Robotics
Abstract
Certain robot missions need to perform predictably in a physical environment that may only be poorly characterized in advance. We have previously developed an approach to establishing performance guarantees for behaviorbased controllers in a process-algebra framework. We extend that work here to include random variables, and we show how our prior results can be used to generate a Dynamic Bayesian Network for the coupled system of program and environment model. Verification is reduced to a filtering problem for this network. Finally, we present validation results that demonstrate the effectiveness of the verification of a multiple waypoint robot mission using this approach.
Article Number
1045
Publication Date
11-2013
Recommended Citation
Lyons, Damian M.; Arkin, Ronald C.; Nirmal, Paramesh; Jiang, Shu; Liu, Tsung-Ming; and Deeb, J., "Getting it Right the First time: Robot Mission Guarantees in the Presence of Uncertainty" (2013). Faculty Publications. 36.
https://research.library.fordham.edu/frcv_facultypubs/36
Comments
Intelligent Robots and Systems (IROS) 2013, Tokyo, Japan
This research was conducted at the Fordham University Robotics and Computer Vision Lab. For more information about graduate programs in Computer Science, see http://www.cis.fordham.edu/graduate.html, and the Fordham University Graduate School of Arts and Sciences, see http://www.fordham.edu/gsas.