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首页> 外文期刊>International Journal of Advanced Robotic Systems >The random exploration graph for optimal exploration of unknown environments
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The random exploration graph for optimal exploration of unknown environments

机译:随机探索图,以了解未知环境的最佳探索

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摘要

The exploration of an unknown environment by a robot system is a well-studied problem in robotics; however, although many of the proposals made in this field represent efficient tools in terms of exploration paradigm, most of them are not efficient for time critical applications since the robot may visit the same place more than once during backtracking. In this way and considering these limitations, this article presents a novel approach called the random exploration graph, which addresses the problem of exploring unknown environments by building a graph structure created incrementally by the random choice of the free frontier in the observation range of the robot. In addition, the random exploration graph algorithm uses a new concept called "frontier control'' introduced in this work, used to store nodes left behind in the graph structure that have not been fully explored and that will be used to guide the exploration process in an efficient way, when the algorithm needs to go back to previously visited areas to continue exploration. The frontier control concept next to the versatility of the graph structure used for the exploration process is the main contribution of this work.
机译:通过机器人系统对未知环境的探索是在机器人学中熟练的问题;然而,尽管该字段中的许多提案代表了探索范例的有效工具,但是由于机器人在回溯期间,大多数它们对于时间关键应用来说,它们的大多数是不高效的。通过这种方式并考虑这些限制,本文提出了一种称为随机探索图的新方法,它通过构建通过机器人的观察范围的自由前沿的随机选择创建的图形结构来解决未知环境的问题。此外,随机探索图算法使用该工作中引入的“Frontier Control”的新概念,用于将留下留下的节点存储在未完全探索的图形结构中,将用于指导勘探过程一种有效的方式,当算法需要返回以前访问的区域以继续探索。前沿控制概念旁边用于探索过程的图形结构的多功能性是这项工作的主要贡献。

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