Da Vinci tool torque mapping over 50,000 grasps and its implications on grip force estimation accuracy

Nathan J. Kong, Trevor K. Stephens, Timothy M Kowalewski

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

Despite the increasing use of the da Vinci surgical robot, clinicians often claim that the inclusion of force measurement at the grasper could enhance the use of these robots in surgery. Many methods have been proposed to accurately estimate this force using already-existing sensors on the da Vinci robot. However, a key weakness in these methods is that they rely on a training dataset which was likely obtained at the beginning of a tool's life, and does not accurately represent the state of the tool throughout use. This work aims to address this problem by assessing the grip force estimation error over the lifetime of a single da Vinci tool, and to propose a method to maintain this estimation error at less than 2 mNm. We found that the most significant changes in the tool were seen in the first 1,000 grasps. Despite these changes, our method to periodically retrain our algorithm maintained the error under 2 mNm. An accurate estimation error has implications in haptics as well as obtaining in-vivo tissue properties during surgical procedures.

Original languageEnglish (US)
Title of host publication2018 International Symposium on Medical Robotics, ISMR 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-6
Number of pages6
ISBN (Electronic)9781538625125
DOIs
StatePublished - Apr 6 2018
Event2018 International Symposium on Medical Robotics, ISMR 2018 - Atlanta, United States
Duration: Mar 1 2018Mar 3 2018

Publication series

Name2018 International Symposium on Medical Robotics, ISMR 2018
Volume2018-January

Other

Other2018 International Symposium on Medical Robotics, ISMR 2018
CountryUnited States
CityAtlanta
Period3/1/183/3/18

Fingerprint

Torque
Error analysis
Robots
Force measurement
Surgery
Tissue
Sensors

Cite this

Kong, N. J., Stephens, T. K., & Kowalewski, T. M. (2018). Da Vinci tool torque mapping over 50,000 grasps and its implications on grip force estimation accuracy. In 2018 International Symposium on Medical Robotics, ISMR 2018 (pp. 1-6). (2018 International Symposium on Medical Robotics, ISMR 2018; Vol. 2018-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ISMR.2018.8333292

Da Vinci tool torque mapping over 50,000 grasps and its implications on grip force estimation accuracy. / Kong, Nathan J.; Stephens, Trevor K.; Kowalewski, Timothy M.

2018 International Symposium on Medical Robotics, ISMR 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1-6 (2018 International Symposium on Medical Robotics, ISMR 2018; Vol. 2018-January).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Kong, NJ, Stephens, TK & Kowalewski, TM 2018, Da Vinci tool torque mapping over 50,000 grasps and its implications on grip force estimation accuracy. in 2018 International Symposium on Medical Robotics, ISMR 2018. 2018 International Symposium on Medical Robotics, ISMR 2018, vol. 2018-January, Institute of Electrical and Electronics Engineers Inc., pp. 1-6, 2018 International Symposium on Medical Robotics, ISMR 2018, Atlanta, United States, 3/1/18. https://doi.org/10.1109/ISMR.2018.8333292
Kong NJ, Stephens TK, Kowalewski TM. Da Vinci tool torque mapping over 50,000 grasps and its implications on grip force estimation accuracy. In 2018 International Symposium on Medical Robotics, ISMR 2018. Institute of Electrical and Electronics Engineers Inc. 2018. p. 1-6. (2018 International Symposium on Medical Robotics, ISMR 2018). https://doi.org/10.1109/ISMR.2018.8333292
Kong, Nathan J. ; Stephens, Trevor K. ; Kowalewski, Timothy M. / Da Vinci tool torque mapping over 50,000 grasps and its implications on grip force estimation accuracy. 2018 International Symposium on Medical Robotics, ISMR 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 1-6 (2018 International Symposium on Medical Robotics, ISMR 2018).
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