An important capability of humans when performing dexterous precision gripping tasks is our ability to feel both the weight and slipperiness of an object in real-time, and adjust our grip force accordingly. In this paper, we present for the first time a fully-instrumented version of our PapillArray tactile sensor concept, which can sense grip force, object weight, and incipient slip and friction, all in real-time. We demonstrate the real-time estimation of friction and measurement of 3D force from PapillArray sensors mounted on each finger of a two-finger gripper, combined with a closed-loop grip-force control algorithm that dynamically applies a near-optimal grip force to avoid dropping objects of varying weight and friction. A vertical lifting task was performed using an object with varying weight and friction, and with some common household items. After intentionally adding a 20% safety margin on the target grip force, the actual grip force applied was only 9-30 % greater than that required to avoid slip. Future work will focus on incorporating real-time torque measurement into the grip force feedback control. This will significantly advance the state-of-the-art in artificial tactile sensing and bring us closer to robotic dexterity.
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Real-time Friction Estimation for Grip Force Control
Semantic Scholar · Engineering · 2021
Abstract
An important capability of humans when performing dexterous precision gripping tasks is our ability to feel both the weight and slipperiness of an object in real-time, and adjust our grip force accordingly. In this paper, we present for the first time a fully-instrumented version of our PapillArray tactile sensor concept, which can sense grip force, object weight, and incipient slip and friction, all in real-time. We demonstrate the real-time estimation of friction and measurement of 3D force from PapillArray sensors mounted on each finger of a two-finger gripper, combined with a closed-loop grip-force control algorithm that dynamically applies a near-optimal grip force to avoid dropping objects of varying weight and friction. A vertical lifting task was performed using an object with varying weight and friction, and with some common household items. After intentionally adding a 20% safety margin on the target grip force, the actual grip force applied was only 9-30 % greater than that required to avoid slip. Future work will focus on incorporating real-time torque measurement into the grip force feedback control. This will significantly advance the state-of-the-art in artificial tactile sensing and bring us closer to robotic dexterity.