Aiming at the problem of efficiency and autonomy of unknown region exploring,an unknown region exploration method based on boundary search idea and suitable for two-dimensional grid map was proposed.The exit area on the boundary in the built environment map was utilized as the logical node and the function value of the node distance was used as the edge weight,to construct the exploration tree of the node to be explored dynamically through traversing,searching,establishing new node and using simultaneous positioning and mapping technology.The robot would be guided to the next exploration area,to complete the independent exploration of the unknown area.The theoretical analysis and simulation results show that with the same experimental map,moving speed of robot and the maximum effective range of the sensor data,compared with other commonly used unknown region exploration algorithm for robots,the single exploration coverage of the proposed method is much higher,so is its exploration efficiency.Logically,the proposed method is a depth-first search traversal of the minimum spanning tree corresponding to the raster map,where each exploration chooses a clear target area,and there is not multiple coverage and falling into the loop,so it is more efficient and stable.%针对移动机器人未知区域探索的效率和自主性等问题,提出了一种基于边界搜寻思想并适用于二维栅格地图的未知区域探索方法.为了使机器人对未知环境的探索更加高效,该方法以已建环境地图中边界上的出口区域作为逻辑节点,以节点距离评价函数值为边权重,动态建立待探索出口区域节点的探索树并通过对探索树的遍历、搜索、回溯和建立新节点的过程,利用同时定位与建图技术,引导机器人有目标地选择下一个探索区域,完成对未知区域的自主探索.理论分析和仿真实验表明,在实验地图、机器人移动速度及传感器数据最大有效范围均相同的情况下,本方法的单次探索覆盖率相比其他常用的机器人未知区域探索算法所得到的单次探索覆盖率即探索效率有大幅提升;且在逻辑上,本方法是对栅格地图对应的最小生成树的深度优先搜索遍历,每次探索都会自主选择明确的目标区域,不会出现多次覆盖和陷入回路的情况,探索性能更加高效和稳定.
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