Probe-to-Grasp Manipulation Using Self-Sensing Pneumatic Variable-Stiffness Joints
Ngoc Duy Tran, Yeman Fan, Feng Dai, Khang Nguyen, Anh Nguyen, Hoang Hiep Ly, Tung D. Ta, Shigeru Chiba

TL;DR
This paper introduces a low-cost, self-sensing pneumatic gripper system that estimates object stiffness through probing, enabling more effective and gentle grasping of deformable objects with spatially varying stiffness.
Contribution
The work presents a novel soft-rigid hybrid gripper with internal pressure sensing for estimating object stiffness, improving soft manipulation and grasping strategies.
Findings
Validated the self-sensing model through stiffness characterization experiments.
Demonstrated effective stiffness-aware probing and grasping on fruits with varying stiffness.
Proposed a practical, low-cost approach for stiffness estimation in soft robotics.
Abstract
Grasping deformable objects with varying stiffness remains a significant challenge in robotics. Estimating the local stiffness of a target object is important for determining an optimal grasp pose that enables stable pickup without damaging the object. This paper presents a probe-to-grasp manipulation framework for estimating the relative stiffness of objects using a passive soft-rigid two-finger hybrid gripper equipped with self-sensing pneumatic variable-stiffness joints. Each finger of the gripper consists of two rigid links connected by a soft pneumatic ring placed at the joint, enabling both compliant interaction and controllable joint stiffness via internal pressurization. By measuring the pressure inside the pneumatic ring, we can estimate the interaction force during contact. Building on this, we propose a practical probing strategy to infer relative object stiffness by…
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