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Abstract
Abstract
This paper introduces RoTipBot, a novel robotic system for handling thin, flexible objects. Different from previous works that are limited to singulating them using suction cups or soft grippers, RoTipBot can grasp and count multiple layers simultaneously, emulating human handling in various environments. Specifically, we develop a novel vision-based tactile sensor named RoTip that can rotate and sense contact information around its tip. Equipped with two RoTip sensors, RoTipBot feeds multiple layers of thin, flexible objects into the centre between its fingers, enabling effective grasping and counting. RoTip's tactile sensing ensures both fingers maintain good contact with the object and accurate tactile counting, and an adjustment approach is designed to allow the gripper to adapt to changes in the object.
(a) A demonstration of RoTipBot. The tactile sensors ensure good contact with objects, while the rotation capability feeds multiple layers of thin, flexible objects into the centre for grasping and counting. Different transparencies of the paper represent states at different time steps. (b) Snapshots of the feeding process for multiple print papers. (c)-(e) Sketches comparing RoTipBot to approaches based on suction cups and soft grippers. RoTipBot can grasp and count multiple layers, whereas the other methods cannot.
The RoTip Sensor
The RoTip Sensor
From Left to Right: (a) Design overview of the RoTip sensor, and the exploded view of RoTip's three modules: (b) fixing module that serves as the structural backbone, ensuring stability and interconnection among sensor components; (c) transmission module that facilitates rotational movement, enabling dynamic functionality; and (d) finger body that constitutes the tactile interface, providing the tactile sensing capabilities.
Methodology
Methodology
An overview of our RoTipBot for thin and flexible handling. (a) Vision-Based Grasping Generation: Given an RGB-D image obtained from a camera, we generate the grasp proposal for guiding the robot to contact and grasp the object. (b) Tactile-based Adjustment for Two-finger Sufficient Contact: To compensate for the noise from visual perception, RoTip’s sensing capability is then utilised to adjust the robot’s end-effector. Once both RoTip sensors are in contact with the object, the end-effector will be rotated around its $x$-axis to an angle inclined to the object for feeding and grasping. (c) Continuous Adjustment: A continuous pose adjustment approach is proposed to ensure two-finger contact while feeding multiple thin and flexible objects. (d) Object Grasping: Finally, the gripper is closed to pick up the objects.
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