Cody Narber

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About

Cody Narber is a leading researcher in human–robot collaboration, with a focus on enabling seamless teamwork between humans and autonomous systems. His work addresses the fundamental challenge of bridging cognitive and physical differences between human and robotic teammates, particularly in high-stakes environments. Narber’s most cited paper, “Human modeling for human–robot collaboration” (2017, 55 citations), introduces frameworks for robots to understand and predict human behavior, a critical step toward intuitive and effective collaboration. He further extends this work into extreme operational contexts, as demonstrated in “Touch recognition and learning from demonstration (LfD) for collaborative human-robot firefighting teams” (2016, 6 citations). This research pioneers the use of tactile communication—a vital channel in noisy, visually obscured environments like Navy ship fires—to allow robots to learn from human demonstrations and respond to non-verbal cues. By integrating touch recognition with learning from demonstration, Narber’s work directly supports the development of robotic teammates that can operate reliably in chaotic, real-world scenarios. His contributions are shaping the future of human-robot teams in defense, emergency response, and industrial settings, where trust and mutual understanding are paramount.