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Exploration via structured triangulation by a multi-robot system with bearing-only low-resolution sensors

机译:通过仅带轴承的低分辨率传感器的多机器人系统通过结构化三角测量进行探索

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This paper presents a distributed approach for exploring and triangulating an unknown region using a multirobot system. The resulting triangulation is a physical data structure that is a: compact representation of the workspace, contains distributed knowledge of each triangle, builds the dual graph of the triangulation, and supports reads and writes of auxiliary data. Our algorithm builds a triangulation in a closed two-dimensional Euclidean environment, starting from a single location. It provides coverage with a breadth-first search pattern and completeness guarantees. We show that the computational and communication requirements to build and maintain the triangulation and its dual graph are small. We then present a physical navigation algorithm that uses the dual graph, and show that the resulting path lengths are within a constant factor of the shortest-path Euclidean distance. Finally, we validate our theoretical results with experiments on triangulating a region with a system of low-cost robots. Analysis of the resulting triangulation shows that most of the triangles are of high quality, and cover a large area. Implementation of the triangulation, dual graph, and navigation all use communication messages of fixed size, and are a practical solution for large populations of low-cost robots.
机译:本文提出了一种使用多机器人系统探索和三角剖分未知区域的分布式方法。生成的三角剖分是一种物理数据结构,它是:工作区的紧凑表示,包含每个三角形的分布式知识,构建三角剖分的对偶图,并支持辅助数据的读取和写入。我们的算法从单个位置开始在封闭的二维欧几里德环境中建立三角剖分。它以广度优先的搜索模式提供覆盖范围,并保证完整性。我们表明,建立和维护三角剖分及其对偶图的计算和通信需求很小。然后,我们提出一种使用对偶图的物理导航算法,并证明所得到的路径长度在最短路径欧氏距离的恒定因子之内。最后,我们通过使用低成本机器人系统对区域进行三角剖分的实验来验证我们的理论结果。对生成的三角剖分的分析表明,大多数三角形都是高质量的,并且覆盖的面积很大。三角剖分,对偶图和导航的实现均使用固定大小的通信消息,并且是针对大量低成本机器人的实用解决方案。

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