基于改进RRT*算法的肺活检路径规划

Yuexi Dong, Kun Wang, Zhen Yang, S. Fok, Han Wang
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引用次数: 0

摘要

路径规划在机器人辅助的经皮穿刺中起着核心作用。路径规划的主要挑战在于针的几何和力学运动约束,以及人体复杂的解剖环境。在非完整规划中,经典的快速探索随机树(RRT)算法可能无法提供连续且可避免障碍的路径。为了在曲率可控导向针的基础上寻找可行路径并使其对软组织的损伤最小化,我们提出了一种利用RRT*和二次Bezier曲线平滑技术的方法。使用Bezier曲线平滑的RRT*可以生成由连续连接的光滑分段平面曲线组成的路径。比较表明,我们的方法生成的路径更短,更少痛苦,成功率更高。
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Path Planning with Modified RRT* Algorithm for Lung Biopsy
– Path planning plays a central role in robot-assisted percutaneous insertion. The main challenge of path planning exists in the motion constraints inherited from the geometry and mechanics of the needle, and the complex anatomic environment of human body. In nonholonomic planning, the classic Rapidly-Exploring Random Trees (RRT) algorithm may fail to provide a continuous and obstacle-avoidable path. To find a feasible path and minimize the damage on soft tissues based on a newly-introduced curvature-controllable steerable needle, we propose a method that utilizes RRT* and quadratic Bezier curve smoothing technique. RRT* with Bezier Curve Smoothing can generate a path composed of smooth piecewise planar curves with continuous connections. Comparisons are employed to show that our method generates shorter and less torturous paths with a higher success rate.
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