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About

Greg Chance is a robotics researcher whose work sits at the intersection of assistive robotics, human-robot interaction, and robot safety. He is perhaps best known for his sustained focus on robot-assisted dressing — a deceptively complex challenge requiring robots to work in intimate physical proximity with users who may have diverse physical abilities and conditions. His 2018 paper on personalized robot assistants for dressing support (59 citations) represents a landmark contribution to user-adaptive robotics, highlighting the critical importance of tailoring robotic systems to individual users rather than assuming a one-size-fits-all approach. Alongside this, his work on dressing dynamics, pose tracking under occlusion, and error-handling strategies has collectively helped establish a rigorous scientific foundation for safe, practical assistive robots in caregiving contexts. Chance has also made meaningful contributions to robot safety assessment, applying methods like HAZOP and STPA to assistive systems, and more recently has expanded his scope to swarm robotics, exploring trustworthiness and safety assurance for emergent multi-robot behaviors. His research speaks directly to one of society's most pressing challenges — supporting an aging population — making it both technically sophisticated and profoundly human in its motivation.