代码链接: https://github.com/NKU-MobFly-Robotics/CURE1 

论文连接: https://ieeexplore.ieee.org/document/10155622

视频连接: https://www.bilibili.com/video/BV1oB4zeeEDm/?spm_id_from=333.1387.homepage.video_card.click&vd_source=0e7c59dd804a18d9a9c201eafe9ac6e5

 CURE：Centroids of Unknown Regions Exploration

        首创"【区域引导】”未知环境探索，突破边界局部视野局限，大幅提升探索效率；简单轻量化代码设计，可实现快速部署运行。目前CURE1适用于室内平坦场景，未来CURE2将扩展至野外大范围崎岖场景，并显著减少通信量。

        Q. Bi, X. Zhang*, et al. CURE: A hierarchical framework for Multi-Robot autonomous exploration inspired by centroids of unknown regions, IEEE Transactions on Automation Science and Engineering(T-ASE), 2024, 21(3): 3773-3786 (论文2022年11月提交，2023年6月在线发表)

Abstract

     In this paper, a novel multi-robot autonomous exploration approach CURE is proposed based on dynamic Voronoi diagrams and centroids of unknown connected regions. Compared with existing approaches, the novelty of this work is twofold: 1) Dynamic Voronoi diagram is used for partition of the space being explored to improve the efffciency of multirobot exploration, and then a new parameter-insensitive utility function is elaborately designed to evaluate the information of centroids, which helps guide the robot to explore unknown regions. 2) A hierarchical framework consisting of global and local exploration windows for detecting centroids is designed, wherein the global exploration window is activated to find centroids to guide the robot exploration when there are no centroids in any one local exploration window. We validate the feasibility and exploration efficiency of the proposed approach in various complex simulation scenarios and challenging realworld tasks. All test results show that the exploration time consumption and path cost are reduced by up to 50.7% and 34.4%, respectively, compared with an advanced RRT-based multi-robot exploration approach.