Roadmap is important in typical robotic applications and it is not a trivial task to obtain in unknown space. In this paper, we propose a novel approach to calculate the roadmap that is robust against noisy environmental contours and the movement of the robot. In order to obtain full visibility to space, we design a direct space partitioning approach to produce the roadmap. It uses readings from rangefinders to establish sequential polygons in time, and as the robot moves, intersections among polygons are iteratively obtained. After iterations of updates, we obtain a number of polygons with stable forms. Based on the connections among the polygons, we obtain a roadmap and propose a routing algorithm to calculate paths between points in space. Simulation examples are provided to demonstrate the performance of the proposed approach.

路线图在典型的机器人应用中很重要，在未知的空间中获取并非易事。在本文中，我们提出了一种新颖的方法来计算路线图，该路线图可抵抗嘈杂的环境轮廓和机器人的运动。为了获得对空间的完全可见性，我们设计了一种直接的空间划分方法来生成路线图。它使用测距仪的读数来及时建立顺序的多边形，并且随着机器人的移动，迭代地获得多边形之间的交点。更新迭代后，我们获得了许多具有稳定形式的多边形。基于多边形之间的连接，我们获得了路线图并提出了一种路由算法来计算空间中点之间的路径。提供了仿真示例，以演示所提出方法的性能。