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An architecture for multi-robot hector mapping

机译:多机器人海克特映射的架构

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Urban search and rescue robots explore the area which they don't know. They must localize themselves, map the environment, and choose their targets. The usage of robot teams can be very effective for large areas instead of a single robot. Robot teams can be managed with distributed or centric methodologies. In a distributed architecture, each robot should be self-sufficient by means of all search tasks. This also means that each robot needs a rich computational power. Moreover, an optimal exploration strategy requires communication between all the robots. A common way to get such an architecture is applying centric approaches. In centric approaches, each robot can be seen as a mobile sensor with little computational power. They send their measures to the center. The map is generated at the center. Navigation commands are generated at the center according to the exploration strategy. ROS is a very common platform for robotic researchers. It includes several single robot mapping algorithms. But, there is no common mapping algorithm for centric approaches. In this study, we developed a multi-robot version of Hector mapping which is widely used in most robotic researches. For the real-time running ability, we parallelized its optimization procedure. The experimental results shows the effectiveness of our proposed architecture.
机译:城市搜索和救援机器人会探索他们不知道的区域。他们必须定位自己,绘制环境图并选择目标。机器人团队的使用对于大面积而不是单个机器人可能非常有效。可以使用分布式或中心方法来管理机器人团队。在分布式体系结构中,每个机器人都应通过所有搜索任务自给自足。这也意味着每个机器人都需要强大的计算能力。此外,最佳的探索策略要求所有机器人之间进行通信。获得这种架构的一种常见方法是应用中心方法。在中心方法中,每个机器人都可以看作是具有很少计算能力的移动传感器。他们将措施发送到中心。地图在中心生成。导航命令是根据探索策略在中心生成的。 ROS是机器人研究人员非常常用的平台。它包括几种单个机器人映射算法。但是,对于中心方法没有通用的映射算法。在这项研究中,我们开发了Hector映射的多机器人版本,该版本已在大多数机器人研究中广泛使用。对于实时运行能力,我们对其优化过程进行了并行处理。实验结果表明了我们提出的体系结构的有效性。

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