Robotics, Formal Verification, Validation, Behavior-Based
Artificial Intelligence and Robotics | 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 behavior-based 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.
IEEE/RSJ Int. Conference on Intelligent Robots and Systems (IROS) 2013, Tokyo, Japan, November 2013.
Lyons, Damian; Arkin, Ron; Nirmal, Paramesh; Jiang, Shu; Liu, Tsung-Ming; and Deeb, Julia, "Getting it Right the First time: Robot Mission Guarantees in the Presence of Uncertainty" (2013). Faculty Publications. 62.
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