title: Estimation of environmental force for the haptic interface of robotic surgery.
abstract: BACKGROUND
  The success of a telerobotic surgery system with haptic feedback requires accurate force-tracking and position-tracking capacity of the slave robot. The two-channel force-position control architecture is widely used in teleoperation systems with haptic feedback for its better force-tracking characteristics and superior position-tracking capacity for the maximum stability margin. This control architecture, however, requires force sensors at the end-effector of the slave robot to measure the environment force. However, it is difficult to attach force sensors to slave robots, mainly due to their large size, insulation issues and also large currents often flowing through the end-effector for incision or cautery of tissues.
  
  
  METHODS
  This paper provides a method to estimate the environment force, using a function parameter matrix and a recursive least-squares method. The estimated force is used to feed back the force information to the surgeon through the control architecture without involving the force sensors.
  
  
  RESULTS
  The simulation and experimental results verify the efficacy of the proposed method. The force estimation error is negligible and the slave device successfully tracks the position of the master device while the stability of the teleoperation system is maintained.
  
  
  CONCLUSIONS
  The developed method allows practical haptic feedback for telerobotic surgery systems in the two-channel force-position control scheme without the direct employment of force sensors at the end-effector of the slave robot.
authors.affiliation: Department of Human Perception, Cognition and Action, Max Planck Institute for Biological Cybernetics, Tübingen, Germany.
authors.forename: Hyoung Il
authors.initials: HI
authors.lastname: Son
authors.forename: Tapomayukh
authors.initials: T
authors.lastname: Bhattacharjee
authors.forename: Doo Yong
authors.initials: DY
authors.lastname: Lee
mesh_terms: D001698:Biomedical Engineering / Q000295:instrumentation; D005246:Feedback; D016018:Least-Squares Analysis; D012044:Regression Analysis; D012984:Software