A Dexterous Reorientation Strategy for Precision Picking of Large Thin Objects

This paper presents tilt-and-pivot manipulation, a robotic technique for picking large, thin objects resting on hard supporting surfaces. The method employs in-hand dexterous manipulation by reorienting the gripper around the object's contact point, allowing a finger to enter the gap between the object and the surface, without requiring relative sliding at the contact. This finally facilitates reliable pinch grasps on the object's faces. We investigate the kinematic principles and planning strategies underlying tilt-and-pivot, discuss effector design considerations, and highlight the practical advantages of the strategy, which is applicable to a variety of low-profile objects. Experimental results, incorporating vision and force-torque sensing, demonstrate its effectiveness in bin-picking scenarios and its applicability to more complex object-handling tasks.

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Publication Details

Journal
Sensors
Published
2025-10-21
DOI
https://doi.org/10.3390/s25206496
Primary Topic
Robot Manipulation and Learning
Type
article
Field-Weighted Citation Impact
0.00
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article

A Dexterous Reorientation Strategy for Precision Picking of Large Thin Objects

Jungwon Seo
Sensors
Robot Manipulation and Learning
article

A Dexterous Reorientation Strategy for Precision Picking of Large Thin Objects

Jungwon Seo
article en

Abstract

This paper presents tilt-and-pivot manipulation, a robotic technique for picking large, thin objects resting on hard supporting surfaces. The method employs in-hand dexterous manipulation by reorienting the gripper around the object's contact point, allowing a finger to enter the gap between the object and the surface, without requiring relative sliding at the contact. This finally facilitates reliable pinch grasps on the object's faces. We investigate the kinematic principles and planning strategies underlying tilt-and-pivot, discuss effector design considerations, and highlight the practical advantages of the strategy, which is applicable to a variety of low-profile objects. Experimental results, incorporating vision and force-torque sensing, demonstrate its effectiveness in bin-picking scenarios and its applicability to more complex object-handling tasks.

SensorsVol. 25(20)
Pusan National University (KR)
Openalex Percentile: Top 61%
Robot Manipulation and Learning
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