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About

Andrew Coles is a leading researcher at the intersection of artificial intelligence, robotics, and human-robot interaction, with a particular focus on explainable AI and autonomous space robotics. His work addresses a fundamental challenge: making robots not only capable of autonomous decision-making but also understandable and trustworthy to humans. Coles spearheaded the development of the ERGO (European Robotic Goal-Oriented Autonomous Controller) framework, a major European initiative for enhancing robot autonomy in space missions, including applications for ExoMars and Mars2020. His research on on-board planning using temporal PDDL has been pivotal for enabling robots to operate independently in computationally constrained space environments. Coles’s most influential work investigates when and why users seek explanations from robots, with his 2024 paper on this topic already garnering 19 citations. He has also pioneered methods for domain-independent verbalization of task plans (PlanVerb) and developed taxonomies of explanation types for human-agent collaboration. His recent contributions include using time series classification to detect interaction ruptures in HRI and evaluating whether large language models align with social intuitions for human-robot interactions. Through this body of work, Coles is shaping the future of transparent, socially-aware autonomous systems.