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首页> 外文期刊>Mathematical Problems in Engineering >Distributed Multirobot Exploration Based on Scene Partitioning and Frontier Selection
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Distributed Multirobot Exploration Based on Scene Partitioning and Frontier Selection

机译：基于场景划分和边界选择的分布式多机器人探索

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In mobile robotics, the exploration task consists of navigating through an unknown environment and building a representation of it. The mobile robot community has developed many approaches to solve this problem. These methods are mainly based on two key ideas. The first one is the selection of promising regions to explore and the second is the minimization of a cost function involving the distance traveled by the robots, the time it takes for them to finish the exploration, and others. An option to solve the exploration problem is the use of multiple robots to reduce the time needed for the task and to add fault tolerance to the system. We propose a new method to explore unknown areas, by using a scene partitioning scheme and assigning weights to the frontiers between explored and unknown areas. Energy consumption is always a concern during the exploration, for this reason our method is a distributed algorithm, which helps to reduce the number of communications between robots. By using this approach, we also effectively reduce the time needed to explore unknown regions and the distance traveled by each robot. We performed comparisons of our approach with state-of-the-art methods, obtaining a visible advantage over other works.
机译：在移动机器人中，探索任务包括在未知环境中导航并构建其表示形式。移动机器人社区已开发出许多方法来解决此问题。这些方法主要基于两个关键思想。第一个是选择要探索的有希望的区域，第二个是使成本函数最小化，其中涉及机器人行走的距离，完成探索所需的时间等。解决探索问题的一种选择是使用多个机器人来减少任务所需的时间并增加系统的容错能力。我们提出了一种新的方法来探索未知区域，方法是使用场景分区方案并将权重分配给已探索区域和未知区域之间的边界。能源消耗始终是勘探过程中的一个问题，因此，我们的方法是一种分布式算法，有助于减少机器人之间的通信数量。通过使用这种方法，我们还可以有效地减少探索未知区域所需的时间以及每个机器人的行进距离。我们将我们的方法与最先进的方法进行了比较，获得了比其他作品明显的优势。

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