Estimation of Soft Tissue Mechanical Parameters From Robotic Manipulation Data

• Published in: IEEE/ASME transactions on mechatronics Vol. 18; no. 5; pp. 1602 - 1611
• Main Authors: Boonvisut, P., Cavusoglu, M. C.
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.10.2013; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Biological materials; Biological tissues; Computer simulation; Deformable models; Deformation; elasticity; Estimating; Estimation; Finite element analysis; finite element methods; imaging phantoms; manipulators; material properties; Materials; materials testing; Mathematical models; Mechatronics; medical robotics; Parameter estimation; Robot sensing systems; Robotics; Soft tissues; Studies; surgery
• ISSN: 1083-4435; 1941-014X
• DOI: 10.1109/TMECH.2012.2209673

Robotic motion planning algorithms used for task automation in robotic surgical systems rely on the availability of accurate models of target soft tissue's deformation. Relying on generic tissue parameters in constructing the tissue deformation models is problematic because biological tissues are known to have very large (inter- and intrasubject) variability. A priori mechanical characterization (e.g., uniaxial bench test) of the target tissues before a surgical procedure is also not usually practical. In this paper, a method for estimating mechanical parameters of soft tissue from sensory data collected during robotic surgical manipulation is presented. The method uses force data collected from a multiaxial force sensor mounted on the robotic manipulator, and tissue deformation data collected from a stereo camera system. The tissue parameters are then estimated using an inverse finite element method. The effects of measurement and modeling uncertainties on the proposed method are analyzed in simulation. The results of experimental evaluation of the method are also presented.