三维路径规划：基于粗糙分体论的导航
Three-Dimensional Path Planning: Navigating through Rough Mereology
AI总结：
本研究提出基于粗糙分体论的三维飞行机器人路径规划方法，构建三维分体势场算法并辅以加权欧氏距离避局部极小，结合双实时相机与OpenCV搭建环境，旨在将成果应用于无人机导航。
摘要：
本文提出一种基于粗糙分体论的飞行机器人三维环境路径规划创新技术。研究核心目标是构建可在三维空间中生成分体势场的算法，为避免陷入局部极小值，引入加权欧氏距离进行辅助。此外，算法还实现了从起点到目标点的避障路径搜索。实验环境由两台实时工作的相机构建，使用Python库OpenCV（一种计算机视觉库）识别形状与颜色，以确定地图内的通道和环境元素。本文的主要目的是将所得结果应用于无人机。
英文摘要：
In this paper, we present an innovative technique for the path planning of flying robots in a 3D environment in Rough Mereology terms. The main goal was to construct the algorithm that would generate the mereological potential fields in 3-dimensional space. To avoid falling into the local minimum, we assist with a weighted Euclidean distance. Moreover, a searching path from the start point to the target, with respect to avoiding the obstacles was applied. The environment was created by connecting two cameras working in real-time. To determine the gate and elements of the world inside the map was responsible the Python Library OpenCV [1] which recognized shapes and colors. The main purpose of this paper is to apply the given results to drones.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
