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About

Thomas Hummel’s research lies at the intersection of robotic manipulation and human-robot interaction, with a focus on making robots both more dexterous and more socially intuitive. His most influential work, “A Slip Detection and Correction Strategy for Precision Robot Grasping” (79 citations), introduces a groundbreaking grasp force regulation strategy that operates without prior knowledge of object properties or surface characteristics. This slip detection and correction method is universally applicable across various grippers, significantly advancing the reliability of precision grasping in unstructured environments. Hummel has also made substantial contributions to personalised human-robot interaction, particularly in learning scenarios. His 2017 paper on the impact of personalisation (66 citations) explores how robots can model adaptive, user-specific dialogue to foster natural, engaging interactions. Additionally, his work with the Neuro-Inspired Companion (NICO) robot, showcased in “Hey robot, why don't you talk to me?” (16 citations), demonstrates a system that tracks faces, remembers users, and engages in personalised conversation. Through these contributions, Hummel has advanced both the physical and social capabilities of robots, with his slip detection strategy standing as a particularly notable achievement for its broad applicability and impact on precision manipulation.