变刚度仿人灵巧手的设计与建模

康荣杰 ,  傅云龙 ,  杨尚奎 ,  李晨宁 ,  李岩

天津大学学报(自然科学与工程技术版) ›› 2026, Vol. 59 ›› Issue (7) : 677 -688.

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天津大学学报(自然科学与工程技术版) ›› 2026, Vol. 59 ›› Issue (7) : 677 -688. DOI: 10.11784/tdxbz202502012

变刚度仿人灵巧手的设计与建模

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Design and Modeling of Variable Stiffness Humanoid Dexterous Hand

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摘要

本文提出了一种具有触觉传感的变刚度灵巧手,旨在提升灵巧手在复杂操作中的适应性和精度.灵巧手采用的刚柔混合设计结合了传统刚性和新型柔性的优点,主要体现在刚性手掌和连续体手指上,变刚度设计采用悬臂梁支点变化的变刚度单元来实现灵巧手在不同任务中的刚度调节,并在指尖加入了触觉传感系统.其次,进行了理论建模,具体包括手指运动学模型、手掌运动学模型以及变刚度单元到连续体手指的刚度映射模型,为灵巧手的运动控制和刚度调节提供了理论支持.然后,根据手指和手掌的运动学模型绘制了灵巧手的工作空间,计算出了灵巧手的弯曲角度范围和侧摆角度范围,与人手形成对比,并进行了刚度映射模型的仿真,分析了影响手指刚度的几个因素.最后,基于以上的设计与分析,搭建了灵巧手样机,并通过实验测试样机的变刚度驱动器性能、手指运动学性能、触觉传感器功能以及刚度映射模型的有效性,从而验证了灵巧手在复杂任务中的运动灵活性和刚度适应性.研究结果表明:该灵巧手具有刚性和柔性的优点,能够通过触觉传感系统提供力反馈,变刚度功能也显著提高了其在不同任务场景下的操作能力,所提出的刚度映射模型能够精准控制手指的刚度,对灵巧手的环境适应性和人机交互安全性具有重要意义.

Abstract

A variable stiffness dexterous hand with tactile sensing was proposed to enhance operational adaptability and accuracy in complex tasks. Adopting a rigid-flexible hybrid design(specifically a rigid palm and continuous finger),the dexterous hand combined the benefits of traditional rigidity and modern flexibility. The variable stiffness design employed a cantilever beam fulcrum unit to actively adjust the stiffness of the hand for diverse tasks. Additionally,a tactile sensing system was integrated into the fingertip. Theoretical models,including finger kinematics,palm kinematics and stiffness mapping models,were developed,connecting the variable stiffness unit to the continuum finger. This offered the theoretical support for motion control and stiffness adjustment. Next,the workspace of the hand was defined based on the finger and palm kinematic models,after which the ranges of its bending and side swing angles were calculated. Further,the stiffness mapping model was simulated,compared with the human hand,to analyze several factors affecting finger stiffness. Finally,a prototype hand was built based on the above design and analysis,and the performances of the variable stiffness actuator,finger kinematics,tactile sensor function,and stiffness mapping models of this prototype were experimentally evaluated,ultimately verifying the flexibility and stiffness adaptabilities of the hand in complex tasks. The results confirmed that the dexterous hand exhibited rigidity and flexibility advantages and could provide force feedback through its tactile sensing system. Further,its variable stiffness function significantly improved its operation ability in diverse task scenarios. Overall,the proposed stiffness mapping model accurately controlled finger stiffness,which was crucial for the environmental adaptability and human-computer interaction safety of dexterous hands.

关键词

灵巧手 / 刚柔混合设计 / 变刚度 / 触觉传感

Key words

dexterous hand / rigid-flexible hybrid design / variable stiffness / tactile sensing

引用本文

引用格式 ▾
康荣杰,傅云龙,杨尚奎,李晨宁,李岩. 变刚度仿人灵巧手的设计与建模[J]. 天津大学学报(自然科学与工程技术版), 2026, 59(7): 677-688 DOI:10.11784/tdxbz202502012

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参考文献

[1]

Wang T M, Tao Y, Liu H. Current researches and future development trend of intelligent robot:A review[J]. International Journal of Automation and Computing, 2018, 15(9):525-546.

[2]

Jacobsen S, Iversen E, Knutti D, et al. Design of the Utah/MIT dextrous hand[C]// IEEE International Conference on Robotics and Automation. San Francisco,USA, 1986:1520-1532.

[3]

Challoo R, Johnson J P, MaLauchlan R A, et al. Intelligent control of a Stanford JPL hand attached to a 4 DOF robot arm[C]// IEEE International Conference on Systems,Man and Cybernetics. San Antonio,USA, 1994:1274-1278.

[4]

Yang Y, Chen Y H, Li Y T, et al. Bioinspired robotic fingers based on pneumatic actuator and 3D printing of smart material[J]. Soft Robotics, 2017, 4(2):147-162.

[5]

Manti M, Hassan T, Passetti G, et al. A bioinspired soft robotic gripper for adaptable and effective grasping[J]. Soft Robotics, 2015, 2(3):107-116.

[6]

Rus D, Tolley M T. Design,fabrication and control of soft robots[J]. Nature, 2015, 521:467-475.

[7]

He Z Y, Lian B B, Song Y M. Rigid—soft coupled robotic gripper for adaptable grasping[J]. Journal of Bionic Engineering, 2023, 20:2601-2618.

[8]

Kang R J, Guo Y, Chen L S, et al. Design of a pneumatic muscle based continuum robot with embedded tendons[J]. IEEE/ASME Transactions on Mechatronics, 2017, 22(2):751-761.

[9]

Liu Z X, Jin H Z, Liu Y B, et al. An online stiffness estimation approach for variable stiffness actuators using lever mechanism[J]. IEEE Robotics and Automation Letters, 2022, 7(3):6709-6717.

[10]

Su Q, Zou Q, Li Y, et al. A stretchable and strain—unperturbed pressure sensor for motion interference—free tactile monitoring on skins[J]. Science Advances, 2021, 7(48):eabi4563.

[11]

Park H, Kim D. An open—source anthropomorphic robot hand system:HRI hand[J]. HardwareX, 2020, 7(2):e00100.

[12]

Li G Z, Liu S Q, Wang L Q, et al. Skin—inspired quadruple tactile sensors integrated on a robot hand enable object recognition[J]. Science Robotics, 2020, 5(49):eabc8134.

[13]

Sarwar M S, Dobashi Y, Preston C, et al. Bend,stretch,and touch:Locating a finger on an actively deformed transparent sensor array[J]. Science Advances, 2017, 3(3):1602200.

[14]

Wang H Y, Wang W Q, Kim J J, et al. An optical—based multipoint 3—axis pressure sensor with a flexible thin—film form[J]. Science Advances, 2023, 9(36):2445.

[15]

Pacchierotti C, Prattichizzo D. Cutaneous/tactile haptic feedback in robotic teleoperation:Motivation,survey,and perspectives[J]. IEEE Transactions on Robotics, 2024, 40:978-998.

[16]

Mao Q, Zhu R. Enhanced robotic tactile perception with spatiotemporal sensing and logical reasoning for robust object recognition[J]. Applied Physics Reviews, 2024, 11(2):021424.

[17]

Kang M Y, Gang C G, Ryu S K, et al. Haptic interface with multimodal tactile sensing and feedback for human—robot interaction[J]. Micro and Nano Systems Letters, 2024, 12:1-9.

[18]

Jiang Y, Fan L, Sun X L, et al. A multifunctional tactile sensory system for robotic intelligent identification and manipulation perception[J]. Advanced Science, 2024, 11(41):2402705.

[19]

Liao J J, Xiong P W, Liu P X, et al. Enhancing robotic tactile exploration with multireceptive graph convolutional networks[J]. IEEE Transactions on Industrial Electronics, 2024, 71(8):9297-9308.

基金资助

国家自然科学基金资助项目(52375023)

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