Haptic Stiffness Perception Using Hand Exoskeletons in Tactile Robotic Telemanipulation

Queen Mary University of London1,University College London2, Humanoid AI3, King’s College London, London, UK.4
Published RA-L 2025 / ICRA 2026

Abstract

Robotic telemanipulation is central in many applications, from healthcare to harsh environments. While visual feedback from cameras can provide valuable information to the human operator, haptic feedback offers insight into certain object properties - such as stiffness - that vision alone cannot provide. However, the use of haptic feedback alone has been largely unexplored. To bridge this gap, we tested ten participants to remotely squeeze soft objects to perceive their stiffness, by teleoperating a dexterous robotic hand using an active hand exoskeleton. Two haptic feedback methods were compared: using only the contact forces measured with the tactile fingertips of the robotic hand, or including a kinematic measure as well (the motion mismatch between the hand exoskeleton and the robotic hand). Our results demonstrate, for the first time, that operators using a hand exoskeleton are indeed capable of discriminating objects of different stiffness relying on haptic feedback alone, with an average accuracy of 75% to identify which object in a pair was most similar to a reference, and 65% to determine which object in a pair was softer. In addition, our findings also suggest that including a kinematic measure in the feedback may enhance discrimination between objects of similar stiffness.

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