A 3D Printing-Enabled Artificially Innervated Smart Soft Gripper with Variable Joint Stiffness

被引:43
作者
Goh, Guo Liang [1 ,2 ]
Goh, Guo Dong
Nguyen, Van Pho [1 ]
Toh, William [1 ]
Lee, Samuel [1 ]
Li, Xin [1 ]
Sunil, Bohra Dhyan [1 ]
Lim, Jian Yee [1 ]
Li, Zhengchen [1 ]
Sinha, Anoop Kumar [1 ]
Yeong, Wai Yee [2 ]
Campolo, Domenico [2 ]
Chow, Wai Tuck [1 ]
Ng, Teng Yong [1 ]
Han, Boon Siew [3 ]
机构
[1] Nanyang Technol Univ, Sch Mech & Aerosp Engn, Singapore 639798, Singapore
[2] Nanyang Technol Univ, Singapore Ctr Printing 3D, Sch Mech & Aerosp Engn, Singapore 639798, Singapore
[3] Nanyang Technol Univ, Schaeffler Hub Adv Res, Singapore 637460, Singapore
关键词
additive manufacturing; multifunctional structures; soft grippers; soft sensors; variable stiffness; SENSORS; MULTIMATERIAL; DESIGN;
D O I
10.1002/admt.202301426
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
The manufacturing industry has witnessed advancements in soft robotics, specifically in robotic grippers for handling fragile or irregular objects. However, challenges remain in balancing shape compliance, structural rigidity, weight, and sensor integration. To address these limitations, a 3D-printed multimaterial gripper design is proposed. This approach utilizes a single, nearly fully automated 3D printing process to create a universal gripper with almost no assembly work. By processing functional polymer, polymer nanocomposite, and metal wire simultaneously, this technique enables multifunctionality. The gripper achieves different gripping configurations by adjusting joint stiffness through Joule heating of conductive polylactic acid material, ensuring shape conformance. Embedded metal wires, created using an in-house wire embedding technique, form reliable high-current-loading interconnections for the conductive joints acting as the heater. Additionally, an integrated soft sensor printed in thermoplastic polyurethane (TPU) and conductive TPU detects compression levels and discerns handled samples. This study showcases the potential of 3D multimaterial printing for on-demand fabrication of a smart universal gripper with variable stiffness and integrated sensors, benefiting the automation industry. Overall, this work presents an effective strategy for designing and fabricating integrated multifunctional structures using soft, rigid, and conductive materials, such as polymer, polymer nanocomposite, and metal through multimaterial 3D printing.
引用
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页数:15
相关论文
共 61 条
[1]   Soft Actuators with Stiffness and Shape Modulation Using 3D-Printed Conductive Polylactic Acid Material [J].
Al-Rubaiai, Mohammed ;
Pinto, Thassyo ;
Qian, Chunqi ;
Tan, Xiaobo .
SOFT ROBOTICS, 2019, 6 (03) :318-332
[2]  
Almurib H. A. F., 2011, 9 INT C ICT KNOWL EN
[3]   Application and integration of an RFID-enabled warehousing management system - a feasibility study [J].
Alyahya, Saleh ;
Wang, Qian ;
Bennett, Nick .
JOURNAL OF INDUSTRIAL INFORMATION INTEGRATION, 2016, 4 :15-25
[4]  
[Anonymous], IND ROB ARMS CHANG W
[5]   Negative Gauge Factor Piezoresistive Composites Based on Polymers Filled with MoS2 Nanosheets [J].
Biccai, Sonia ;
Boland, Conor S. ;
O'Driscoll, Daniel P. ;
Harvey, Andrew ;
Gabbett, Cian ;
O'Suilleabhain, Domhnall R. ;
Griffin, Aideen J. ;
Li, Zheling ;
Young, Robert J. ;
Coleman, Jonathan N. .
ACS NANO, 2019, 13 (06) :6845-6855
[6]   Dexterous Grasping by Manipulability Selection for Mobile Manipulator With Visual Guidance [J].
Chen, Fei ;
Selvaggio, Mario ;
Caldwell, Darwin G. .
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS, 2019, 15 (02) :1202-1210
[7]   A review of soft manipulator research, applications, and opportunities [J].
Chen, Xiaoqian ;
Zhang, Xiang ;
Huang, Yiyong ;
Cao, Lu ;
Liu, Jinguo .
JOURNAL OF FIELD ROBOTICS, 2022, 39 (03) :281-311
[8]  
Cheng X, 2013, PROC INT CONF ANTI
[9]   A 3D Printed Soft Robotic Gripper With a Variable Stiffness Enabled by a Novel Positive Pressure Layer Jamming Technology [J].
Crowley, George B. ;
Zeng, Xianpai ;
Su, Hai-Jun .
IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 7 (02) :5477-5482
[10]   Design of a Soft Gripper With Improved Microfluidic Tactile Sensors for Classification of Deformable Objects [J].
Deng, Linan ;
Shen, Yi ;
Fan, Genglin ;
He, Xin ;
Li, Zhi ;
Yuan, Ye .
IEEE ROBOTICS AND AUTOMATION LETTERS, 2022, 7 (02) :5607-5614