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<p>This research presents the design, optimization, and validation of a soft robotic gripper intended as a multipurpose end effector for the IRB 1410 robot. The gripper is developed using soft silicone materials (Ecoflex 00–30) to ensure safe, adaptive handling of objects with varying shapes and fragility. Emphasizing modularity, the design allows the actuator to function independently or in combination with multiple configurations, increasing its versatility for industrial applications. Finite Element Analysis (FEA) was used to evaluate the mechanical response of the gripper under different pressures. At 200,000&#xa0;Pa, the gripper achieved a deformation of 0.13934&#xa0;m and maintained structural integrity, confirming its resilience under high strain. To optimize performance, the Taguchi method with L9 orthogonal arrays was applied. The optimal conditions 150,000&#xa0;Pa pressure and 1.15&#xa0;g/cm³ material density yielded deformation results closely matching experimental values. ANOVA revealed pressure as the dominant factor (99.9%) influencing deformation. A fuzzy logic-based control system was developed to predict gripper behaviour under varying conditions, achieving less than 5% prediction error. This system supports real-time adaptive control, especially when integrated with IoT-based wireless sensors. A general linear regression model was created to complement the fuzzy system, offering continuous strain prediction based on pressure and material density. This study demonstrates a unified design framework combining FEA, Taguchi analysis, fuzzy logic, and regression modeling to produce a lightweight, flexible, and intelligent soft gripper. The results highlight its potential for next-generation robotic applications in packaging, agriculture, food handling, and other safety-critical environments.</p>

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Design and optimization of a soft gripper based multipurpose end effector for IRB 1410 robot using fuzzy logic and regression Taguchi analysis

  • 期刊论文

  • 发表日期：

    2025年11月11日

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  • Prabhu Sethuramalingam,
  • Uma. M,
  • Tanmay Pharlia,
  • Raghav Garg,
  • M. M. Reddy

摘要

This research presents the design, optimization, and validation of a soft robotic gripper intended as a multipurpose end effector for the IRB 1410 robot. The gripper is developed using soft silicone materials (Ecoflex 00–30) to ensure safe, adaptive handling of objects with varying shapes and fragility. Emphasizing modularity, the design allows the actuator to function independently or in combination with multiple configurations, increasing its versatility for industrial applications. Finite Element Analysis (FEA) was used to evaluate the mechanical response of the gripper under different pressures. At 200,000 Pa, the gripper achieved a deformation of 0.13934 m and maintained structural integrity, confirming its resilience under high strain. To optimize performance, the Taguchi method with L9 orthogonal arrays was applied. The optimal conditions 150,000 Pa pressure and 1.15 g/cm³ material density yielded deformation results closely matching experimental values. ANOVA revealed pressure as the dominant factor (99.9%) influencing deformation. A fuzzy logic-based control system was developed to predict gripper behaviour under varying conditions, achieving less than 5% prediction error. This system supports real-time adaptive control, especially when integrated with IoT-based wireless sensors. A general linear regression model was created to complement the fuzzy system, offering continuous strain prediction based on pressure and material density. This study demonstrates a unified design framework combining FEA, Taguchi analysis, fuzzy logic, and regression modeling to produce a lightweight, flexible, and intelligent soft gripper. The results highlight its potential for next-generation robotic applications in packaging, agriculture, food handling, and other safety-critical environments.