A Tool-Path Interpolation Algorithm Based on Unfolding-Bending Parametric Curves

Fan, Li Cheng; Sun, Li; Du, Zhi Jiang

doi:10.4028/www.scientific.net/kem.407-409.220

Cited by 1 publication

(1 citation statement)

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“…Sugita et al [12] present a trajectory generation strategy based on geometric model and implemented it in a 7axis grinding robot, revealing that the strategy can prevent soft tissue damage. Fan et al [13] propose a parallel grinding and non-interfering trajectory planning method for implant grinding robot, which prevents the interference between the two grinding trajectories, and introduce the quadtree theory to speed up the generation of tool trajectory. Tian et al [14] develop a trajectory generation approach for parameterized modular grinding based on the features of cervical disc replacement and the structure of cervical vertebrae and minimize the damage to the patient through surface and spherical grinding of the implant.…”

Section: Introductionmentioning

confidence: 99%

Grinding Method, Trajectory Planning and Simulation of a 3 DOF Knee Grinding Robot

Tian¹,

Ma²,

Zhu³

et al. 2019

Int. j. simul. model.

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This paper aims to improve the accuracy of robot-assisted grinding in total knee arthroplasty (TKA). For this purpose, a 3 DOF knee grinding robot was designed, combining the merits of series robot and parallel robot. The kinematics equations of the robot were derived by the vector method and the workspace of the robot was identified through Monte-Carlo method. Then, the grinding method of the robot was developed according to the procedure of the TKA. Specifically, the grinding trajectory was planned considering the implant selected for the patient. First, the plane and boundary equations of the implant were determined; then, the femur was ground into the desired shape; after that, the implant was cut off with a ball cutting tool vertically to the depth equal to the row spacing. To validate the trajectory planning method, a simulation analysis was performed on the planned trajectory. The results prove the feasibility and efficiency of the proposed method. The research findings shed new light on the robot-assisted TKA.

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Section: Introductionmentioning

confidence: 99%