Adrian Ball

Papers

Total Citations

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About

Adrian Ball investigates the intersection of robotics and human psychology, with a primary focus on how people perceive and respond to robots in social settings. His work centers on human-robot interaction (HRI), particularly the dynamics of robot approach behavior toward individuals and groups. Ball’s most impactful research quantifies the nuanced comfort levels people experience when a robot approaches them, revealing that being in a group significantly alters one’s sense of ease compared to being alone. His 2014 and 2015 papers, with 18 and 15 citations respectively, established foundational insights into these group versus individual comfort dynamics, involving 140 participants in controlled experiments. He further refined this work in 2017 by determining optimal approach directions for robots interacting with pairs of seated people, using directional statistics like Rayleigh’s test. Beyond approach behavior, Ball has contributed to gesture recognition, comparing unsupervised learning algorithms for clustering human arm gestures to improve robot social capabilities. His research provides essential guidance for designing robots that navigate human spaces with greater social awareness, making him a key voice in creating more comfortable and intuitive human-robot encounters.