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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

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 correlating the estimated normal force with known gripper closing displacement. We validate the self-sensing model through stiffness characterization experiments across bending angles and pressure ranges, and demonstrate stiffness-aware probing-and-grasping in real-life applications: selecting grasp locations on fruits with spatially varying stiffness. The proposed system offers a minimal, low-cost sensing approach for stiffness-aware soft manipulation while retaining probing and grasping capability.

Probe-to-Grasp Manipulation Using Self-Sensing Pneumatic Variable-Stiffness Joints

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 correlating the estimated normal force with known gripper closing displacement. We validate the self-sensing model through stiffness characterization experiments across bending angles and pressure ranges, and demonstrate stiffness-aware probing-and-grasping in real-life applications: selecting grasp locations on fruits with spatially varying stiffness. The proposed system offers a minimal, low-cost sensing approach for stiffness-aware soft manipulation while retaining probing and grasping capability.

Paper Structure

This paper contains 22 sections, 5 equations, 10 figures, 1 table.

Figures (10)

  • Figure 1: Overview of the hybrid gripper mounted on a robotic arm during grasping and probing tasks. (a) The gripper integrates rigid links with a pneumatic soft-ring joint, enabling compliant interaction and variable stiffness control. (b) The hybrid gripper performs a probing process on elongated fruits, such as a banana, to estimate stiffness before grasping. (c) For round fruits such as an orange, the gripper rotates around the object to probe different locations and identify the stiffest region for a stable grasp.
  • Figure 2: Hardware Details: Structural components and dimensions of the newly designed finger and soft pneumatic system. (a) The pneumatic system consists of a pressure sensor and a soft ring, both controlled through the same air channel connected to a solenoid valve. (b) Cross-sectional view of the hybrid finger showing the newly designed fabric-attaching thread mechanism integrated into the finger body. (c) The drawing illustrates the cross-sectional dimensions of the soft core, which includes an additional tube designed to simplify the installation of the silicone tube.
  • Figure 3: System hardware: Experimental platform comprising an xArm 7 robotic arm equipped with a hybrid gripper, a pneumatic supply line with a pressure regulator (SMC CORPORATION), and a control board responsible for command generation, signal interfacing, and overall system integration.
  • Figure 4: Demonstration of the data-collection procedure used to validate stiffness estimation. A force gauge mounted on the robot arm follows a circular trajectory around the joint as the fingertip bends. For each bending angle, the torque $\uptau$ generated by the soft ring is computed from the tangential force $F_t$ and the moment arm length.
  • Figure 5: Pressure variation during the probing process under different initial pressures. Each subplot shows the relationship between the change in pressure and the gripper closing distance for objects with different stiffness levels (Cube 20A, Cube 30A, and Cube 80A). As the closing distance increases, the pressure change becomes more significant for stiffer objects, demonstrating that pressure variation can be used to distinguish relative object stiffness. In addition, the gripper demonstrates higher sensitivity in differentiating stiffness at an initial pressure of 60kPa and a closing distance of approximately 30mm.
  • ...and 5 more figures