Robotics: Science and Systems X

Simultaneous Compliance and Registration Estimation for Robotic Surgery

Siddharth Sanan, Stephen Tully, Andrea Bajo, Nabil Simaan, Howie Choset

Abstract:

Leveraging techniques pioneered by the SLAM community, we present a new filtering approach called simultaneous compliance and registration estimation or CARE. CARE is like SLAM in that it simultaneously determines the pose of a surgical robot while creating a map, but in this case, the map is a compliance map associated with a preoperative model of an organ as opposed to just positional information like landmark locations. The problem assumes that the robot is forcefully contacting and deforming the environment. This palpation has a dual purpose: 1) it provides the necessary geometric information to align or register the robot to \textit{a priori} models, and 2) with palpation at varying forces, the stiffness/compliance of the environment can be computed. By allowing the robot to palpate its environment with varying forces, we create a force balanced spring model within a Kalman filter framework to estimate both tissue and robot position. The probabilistic framework allows for information fusion and computational efficiency. The algorithm is experimentally evaluated using a continuum robot interacting with two bench-top flexible structures.

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Bibtex:

  
@INPROCEEDINGS{Sanan-RSS-14, 
    AUTHOR    = {Siddharth Sanan AND Stephen Tully AND Andrea Bajo AND Nabil Simaan AND Howie Choset}, 
    TITLE     = {Simultaneous Compliance and Registration Estimation for Robotic Surgery}, 
    BOOKTITLE = {Proceedings of Robotics: Science and Systems}, 
    YEAR      = {2014}, 
    ADDRESS   = {Berkeley, USA}, 
    MONTH     = {July},
    DOI       = {10.15607/RSS.2014.X.051} 
}