Florence Hiu Ling Chan

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About

Florence Hiu Ling Chan is a roboticist whose work sits at the intersection of manipulation, force control, and autonomous grasping. Her research focuses on enabling robots to interact with unstructured environments, particularly through the use of force feedback to grasp unknown objects—a critical challenge for real-world automation. Her most cited work, "Learning to Grasp Unknown Objects using Force Feedback" (2017), explores how modern grippers equipped with force sensor arrays can learn to securely handle unfamiliar items by understanding contact kinematics, applied forces, and rigid-body dynamics. Though early in her citation trajectory (4 citations on this paper), the work lays foundational groundwork for adaptive manipulation systems. Chan’s contributions are notable for bridging classical mechanics with learning-based approaches, offering a principled framework for robots to reason about physical interactions. Her research is particularly relevant to industrial automation, assistive robotics, and human-robot collaboration, where safe and reliable grasping remains a bottleneck. As the field moves toward more dexterous and sensor-rich manipulation, Chan’s emphasis on force feedback and contact modeling positions her as a thoughtful contributor to the next generation of physically intelligent robots.