SurgGrip: a compliant 3D printed gripper for vision-based grasping of surgical thin instruments

Jaeseok Kim; Anand Kumar Mishra; Lorenzo Radi; Muhammad Zain Bashir; Olivia Nocentini; Filippo Cavallo

doi:10.1007/s11012-022-01594-6

SurgGrip: a compliant 3D printed gripper for vision-based grasping of surgical thin instruments

Meccanica. 2022;57(11):2733-2748. doi: 10.1007/s11012-022-01594-6. Epub 2022 Oct 30.

Authors

Jaeseok Kim^#¹, Anand Kumar Mishra^#², Lorenzo Radi¹, Muhammad Zain Bashir³, Olivia Nocentini¹, Filippo Cavallo^{1

3}

Affiliations

¹ BioRobotics Institute, Scuola Superiore Sant'Anna, Pisa, Italy.
² Department of Mechanical and Aerospace Engineering, Cornell University, Ithaca, NY 14853 USA.
³ Department of Industrial Engineering, University of Florence, Via Santa Marta 3, 50139 Florence, Italy.

^# Contributed equally.

Abstract

This paper presents a conceptual design and implementation of a soft, compliant 3D printed gripper (SurgGrip), conceived for automated grasping of various surgery-based thin-flat instruments. The proposed solution includes (1) a gripper with a resilient mechanism to increase safety and better adaptation to the unstructured environment; (2) flat fingertips with mortise and tenon joint to facilitate pinching and enveloping based grasping of thin and random shape tools; (3) a soft pad on the fingertips to enable the high surface area to maintain stable grasping of the surgical instruments; (4) a four-bar linkage with a leadscrew mechanism to provide a precise finger movement; (5) enable automated manipulation of surgical tools using computer vision. Our gripper model is designed and fabricated by integrating soft and rigid components through a hybrid approach. The SurgGrip shows passive adaptation through inherent compliance of linear and torsional spring. The four-bar linkage mechanism controlled by a motor-leadscrew-nut drive provides precise gripper opening and closing movements. The experimental results show that the SurgGrip can detect, segment through a camera, and grasp surgical instruments (maximum 606.73 gs), with a 67% success rate (grasped 10 out of 12 selected tools) at 3.21 mm/s grasping speed and 15.81 s object grasping time autonomously. Besides, we demonstrated the pick and place abilities of SurgGrip on flat and nonflat surfaces in real-time.

Supplementary information: The online version contains supplementary material available at 10.1007/s11012-022-01594-6.

Keywords: Compliant hybrid gripper; Grasping; Hospital robots; Robot assistant; Surgical instruments; Thin object manipulation.

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