Zhao Yan-Jiang, Joseph Felix Orlando Maria, Yan Kaiguo, Datla Naresh V, Zhang Yong-De, Podder Tarun K, Hutapea Parsaoran, Dicker Adam, Yu Yan
Annu Int Conf IEEE Eng Med Biol Soc. 2014;2014:380-3. doi: 10.1109/EMBC.2014.6943608.
In robot-assisted needle-based medical procedures, path planning for a flexible needle is challenging with regard to time consumption and searching robustness for the solution due to the nonholonomic motion of the needle tip and the presence of anatomic obstacles and sensitive organs in the intended needle path. We propose a novel and fast path planning algorithm for a robot-assisted active flexible needle. The algorithm is based on Rapidly-Exploring Random Trees combined with reachability-guided strategy and greedy heuristic strategy. Linear segments are taken into consideration to the paths, and insertion orientations are relaxed by the introduction of the linear segments. The proposed algorithm yields superior results as compared to the commonly used algorithm in terms of computational speed, form of path and robustness of searching ability, which potentially can make it suitable for the real-time intraoperative planning for clinical procedures.
在基于机器人辅助的针式医疗手术中，由于针尖的非完整运动以及预期针道中存在解剖障碍物和敏感器官，柔性针的路径规划在时间消耗和解决方案搜索稳健性方面具有挑战性。我们提出了一种新颖且快速的机器人辅助主动柔性针路径规划算法。该算法基于快速扩展随机树，并结合可达性引导策略和贪婪启发式策略。路径中考虑了线性段，通过引入线性段放宽了插入方向。与常用算法相比，该算法在计算速度、路径形式和搜索能力的稳健性方面产生了更优的结果，这可能使其适用于临床手术的实时术中规划。
