Validating an artificial intelligence human proximity operations system with test cases

Justin Huber; Jeremy Straub

doi:10.1117/12.2013647

29 May 2013 Validating an artificial intelligence human proximity operations system with test cases

Justin Huber, Jeremy Straub

Proceedings Volume 8752, Modeling and Simulation for Defense Systems and Applications VIII; 875206 (2013) https://doi.org/10.1117/12.2013647
Event: SPIE Defense, Security, and Sensing, 2013, Baltimore, Maryland, United States

Abstract

An artificial intelligence-controlled robot (AICR) operating in close proximity to humans poses risk to these humans. Validating the performance of an AICR is an ill posed problem, due to the complexity introduced by the erratic (noncomputer) actors. In order to prove the AICR’s usefulness, test cases must be generated to simulate the actions of these actors. This paper discusses AICR’s performance validation in the context of a common human activity, moving through a crowded corridor, using test cases created by an AI use case producer. This test is a two-dimensional simplification relevant to autonomous UAV navigation in the national airspace.

Citation Download Citation

Justin Huber and Jeremy Straub "Validating an artificial intelligence human proximity operations system with test cases", Proc. SPIE 8752, Modeling and Simulation for Defense Systems and Applications VIII, 875206 (29 May 2013); https://doi.org/10.1117/12.2013647

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