External force estimation and implementation in robotically assisted minimally invasive surgery. Issue 2 (3rd May 2017)

• Record Type: Journal Article
• Authors: Sang, Hongqiang; Yun, Jintian; Monfaredi, Reza; Wilson, Emmanuel; Fooladi, Hadi; Cleary, Kevin
• Is Part Of: International journal of medical robotics and computer assisted surgery. Volume 13:Issue 2(2017)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2017-05-03
• Subjects: da Vinci Research Kit (dVRK) -- dynamics -- force estimation -- minimally invasive surgery -- parameter identification; Robotics in medicine -- Periodicals; Surgery -- Technological innovations -- Periodicals; Imaging systems in medicine -- Periodicals; 617.90285
• DOI: 10.1002/rcs.1824
• Languages: English
• ISSNs: 1478-5951

Abstract

Abstract: Background: Robotically assisted minimally invasive surgery can offer many benefits over open surgery and laparoscopic minimally invasive surgery. However, currently, there is no force sensing and force feedback. Methods: This research was implemented using the da Vinci research kit. An external force estimation and implementation method was proposed based on dynamics and motor currents. The dynamics of the Patient Side Manipulator was modeled. The dynamic model was linearly parameterized. The estimation principle of external force was derived. The dynamic parameters were experimentally identified using a least squares method. Results: Several experiments including dynamic parameter identification, joint torque estimation, and external force estimation were performed. The results showed that the proposed method could implement force estimation without using a force sensor. Conclusions: The force estimation method was proposed and implemented and experimental results showed the method worked and was feasible. This method could be used for force sensing in minimally invasive surgical robotics in the future.