基于动态系统路径规划与无监督学习的现实环境自主搜索（英文版）

英文标题：Autonomous search of real-life environments combining dynamical system-based path planning and unsupervised learning中文摘要：本文章提出了一种基于 ROS 框架的混沌路径规划应用程序，该程序通过提供避障技术、混沌轨迹分散和准确覆盖计算等技术，解决了对于限制目标的自主搜索与遍历任务的三大关键问题，其性能可与传统最优路径规划器相媲美，并在多种大小、形状和障碍物密度的真实环境与 Gazebo 模拟中进行了测试。英文摘要：In recent years, advancements have been made towards the goal of usingchaotic coverage path planners for autonomous search and traversal of spaceswith limited environmental cues. However, the state of this field is still inits