Surgical retraction of non-uniform deformable layers of tissue: 2D robot grasping and path planning
R.M.C. Jansen, Kris Hauser, Nuttapong Chentanez, A. Frank van der Stappen, Ken Goldberg
- 发表年份
- 2009
- 引用次数
- 30
摘要
This paper considers robotic automation of a common surgical retraction primitive of exposing an underlying area by grasping and lifting a thin, 3D, possibly inhomogeneous layer of tissue. We present an algorithm that computes a set of stable and secure grasp-and-retract trajectories for a point-jaw gripper moving along a plane, and runs a 3D finite element (FEM) simulation to certify and assess the quality of each trajectory. To compute secure candidate grasp locations, we use a continuous spring model of thin, inhomogeneous deformable objects with linear energy potential. Experiments show that this method produces many of the same grasps as an exhaustive optimization with an FEM mesh, but is orders of magnitude cheaper: our method runs in O(v log v) time, where v is the number of veins, while the FEM computation takes O(pn <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</sup> ) time, where n is the number of nodes in the FEM mesh and p is the number of nodes on its perimeter. Furthermore, we present a constant tissue curvature (CTC) retraction trajectory that distributes strain uniformly around the medial axis of the tissue. 3D FEM simulations show that the CTC achieves retractions with lower tissue strain than circular and linear trajectories. Overall, our algorithm computes and certifies a high-quality retraction in about one minute on a PC.
关键词
相关论文
Statistical Learning Theory
Yuhai Wu, Vladimir Vapnik
1999
Artificial intelligence: a modern approach
1995
Applied Nonlinear Control
Jean-Jacques Slotine, Weiping Li
1991
A new optimizer using particle swarm theory
R.C. Eberhart, James Kennedy
2002