Kevin Kilgour

Papers

Total Citations

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About

Kevin Kilgour’s research lies at the intersection of humanoid robotics and conversational artificial intelligence, with a particular focus on enabling robots to learn and adapt through natural language interaction. His most-cited work, “Towards social integration of humanoid robots by conversational concept learning” (2010, 2 citations), explores how humanoid robots can achieve long-term semantic grounding in dynamic, real-world environments. Kilgour’s key contribution is addressing the challenge of continuous service over extended periods, where robots must handle significant variation in speech and context. By developing methods for conversational concept learning, he has advanced the goal of socially integrating robots into human spaces, allowing them to acquire new knowledge through dialogue rather than pre-programmed instructions. This work is foundational for creating robots that can operate autonomously and adaptively in homes, workplaces, and public settings. While his citation count reflects the niche and emerging nature of this field, Kilgour’s research is notable for its forward-looking approach to human-robot interaction, emphasizing the importance of lifelong learning and social adaptability in autonomous systems. His contributions continue to inspire researchers working on embodied AI and socially intelligent robotics.