Michael Kopack

Papers

Total Citations

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About

Michael Kopack is a researcher whose work sits at the critical intersection of human-robot interaction and explainable AI, with a primary focus on building trust through transparent communication. His most influential contribution, the 2012 paper "Explaining robot actions" (74 citations), pioneered a system that allows robots to answer natural language questions about their own behaviors—for instance, explaining a turn by stating, "I detected a person at the end of the hallway." This work directly addresses the "black box" problem in robotics, making autonomous decisions legible and fostering user confidence. Kopack also developed a novel world model framework (2011) designed to facilitate situated human-robot communication by enabling robots to store and utilize semantic information shared by humans in the same physical environment. This framework enhances mutual knowledge, allowing robots to respond more intelligently to contextual cues. Though his citation counts reflect a focused, early-career impact, Kopack’s contributions are foundational to the growing field of explainable robotics, influencing subsequent work on transparency, trust calibration, and collaborative autonomy. His research remains highly relevant for students and engineers designing robots that must earn human trust through clear, understandable dialogue.