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<p>This paper presents a novel design methodology for structurally reinforcing soft fingers with passive support structures, aiming to enhance mechanical capabilities without compromising compliance. We propose and evaluate multiple reinforcement strategies focusing on continuous sheets made from aluminum (<i>alu</i>) and a serial chain hinge support (<i>hinge</i>). We justify our design choices through both mathematical modeling and experimental validation. The approach emphasizes rapid prototyping using off-the-shelf components such as aluminum sheets and door hinges to ensure practicality and reproducibility. Our findings show that the <i>hinge</i> finger configuration significantly improves the horizontal (HA) and vertical (VA) grasping capabilities of the SofIA gripper. Comprehensive performance evaluation includes payload capacity, lateral deflection, grasping force, and object range. The best evaluated finger configuration has maximum grasping range coverage and achieved a maximum payload of 18.1 N. We further demonstrate the effectiveness of our gripper on the EGAD dataset, showcasing its robustness, functionality and applicability. We also provide general recommendations for the design and implementation of used finger reinforcements in practice. Design files and implementation details are released under an open-source license to encourage wider adoption and collaboration in soft robotics.</p>

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Structurally Reinforced Soft Robotic Fingers: Modeling, Design, and Performance Evaluation

  • 期刊论文

  • 发表日期：

    2026年2月16日

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  • Dario Stuhne,
  • Jelena Vuletić,
  • Matko Orsag

摘要

This paper presents a novel design methodology for structurally reinforcing soft fingers with passive support structures, aiming to enhance mechanical capabilities without compromising compliance. We propose and evaluate multiple reinforcement strategies focusing on continuous sheets made from aluminum (alu) and a serial chain hinge support (hinge). We justify our design choices through both mathematical modeling and experimental validation. The approach emphasizes rapid prototyping using off-the-shelf components such as aluminum sheets and door hinges to ensure practicality and reproducibility. Our findings show that the hinge finger configuration significantly improves the horizontal (HA) and vertical (VA) grasping capabilities of the SofIA gripper. Comprehensive performance evaluation includes payload capacity, lateral deflection, grasping force, and object range. The best evaluated finger configuration has maximum grasping range coverage and achieved a maximum payload of 18.1 N. We further demonstrate the effectiveness of our gripper on the EGAD dataset, showcasing its robustness, functionality and applicability. We also provide general recommendations for the design and implementation of used finger reinforcements in practice. Design files and implementation details are released under an open-source license to encourage wider adoption and collaboration in soft robotics.