Document Type



Computer Engineering | Robotics


Certain robot missions need to perform predictably in a physical en-vironment that may only be poorly characterized in advance. This requirement raises many issues for existing approaches to software verification. An approach based on behavior-based controllers in a process-algebra framework is proposed by Lyons et al [15] to side-step state combinatorics. In this paper we show that this approach can be used to generate a Dynamic Bayesian Network for the problem, and that verification is reduced to a filtering problem for this network. We present validation results for the verification of a multiple waypoint robot mission using this approach.

Article Number


Publication Date



AAMAS ARMS 2013 Workshop on Autonomous Robotics and Multirobot Systems, St. Paul MN, May 6-10 2013

This research was conducted at the Fordham University Robotics and Computer Vision Lab. For more information about graduate programs in Computer Science, see, and the Fordham University Graduate School of Arts and Sciences, see

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