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首页> 外文期刊>Mathematical Problems in Engineering: Theory, Methods and Applications >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:基于场景分区和前沿选择的分布式多机罗探索

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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,探索任务包括通过未知环境导航并构建它的表示。移动机器人社区已经开发出许多方法来解决这个问题。这些方法主要基于两个关键思路。第一个是选择有希望的地区探索,第二个是最小化涉及机器人行驶的距离的成本函数的最小化,它们需要探索的时间和其他函数。解决探索问题的选项是使用多个机器人来减少任务所需的时间并为系统添加容错。我们提出了一种新方法来探索未知区域,通过使用场景分区方案并将权重分配给探索和未知区域之间的边界。能源消耗始终是探索期间的疑虑,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,我们还有效减少探索未知区域所需的时间和每个机器人行驶的距离。我们对我们的方法进行了比较,最先进的方法,获得了其他作品的可见优势。

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