Fuzzy-RRT：用于二维半自主手术机械臂避障的模糊快速探索随机树算法
Fuzzy-RRT for Obstacle Avoidance in a 2-DOF Semi-Autonomous Surgical Robotic Arm
AI总结：
针对星际任务中手术机器人需医生完全控制的问题，提出模糊RRT算法用于二维半自主手术机械臂避障与协作控制，使路径搜索时间提升743%，路径代价提升43%。
摘要：
人工智能驱动的半自主机器人手术对于解决长期星际任务中的医疗挑战至关重要，因为在这些任务中，有限的乘员规模和通信延迟限制了传统手术方法的可行性。当前的机器人手术系统需要外科医生的完全控制，要求丰富的专业知识，并限制了其在太空中的可行性。我们提出了一种基于模糊快速探索随机树算法的改进方法，用于以微型机器人辅助手术系统为模型的两自由度机械臂的避障和协作控制。研究发现，模糊快速探索随机树算法将路径搜索时间提高了743%，路径代价提高了43%。
英文摘要：
AI-driven semi-autonomous robotic surgery is essential for addressing the medical challenges of long-duration interplanetary missions, where limited crew sizes and communication delays restrict traditional surgical approaches. Current robotic surgery systems require full surgeon control, demanding extensive expertise and limiting feasibility in space. We propose a novel adaptation of the Fuzzy Rapidly-exploring Random Tree algorithm for obstacle avoidance and collaborative control in a two-degree-of-freedom robotic arm modeled on the Miniaturized Robotic-Assisted surgical system. It was found that the Fuzzy Rapidly-exploring Random Tree algorithm resulted in an 743 percent improvement to path search time and 43 percent improvement to path cost.
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