Failure Explanation in Privacy-Sensitive Contexts: An Integrated Systems Approach

Sihui Li, Sriram Siva, Terran Mott, Tom Williams, Hao Zhang, Neil Dantam

Abstract: In this paper, we explore how robots can properly explain failures during navigation tasks with privacy concerns. We present an integrated robotics approach to generate visual failure explanations, by combining a language-capable cognitive architecture (for recognizing intent behind commands), an object- and location-based context recognition system (for identifying the locations of people and classifying the context in which those people are situated) and an infeasibility proof-based motion planner (for explaining planning failures on the basis of contextually mediated privacy concerns). The behavior of this integrated system is validated using a series of experiments in a simulated medical environment.