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A sensor-based exploration algorithm for autonomous map generation on mobile robot using kinect

机译:基于传感器的应用基于传感器的移动机器人自主地图生成探讨

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This paper addresses on an autonomous exploration algorithm of unknown environment for mapping. An autonomous indoor carrying robot requires a kind of map as knowledge of the work space in order to efficiently execute the navigation task. SLAM (Simultaneously Localization and Mapping) is widely used as an generating a map. However, the map is based on the premise that humans operate robots equipped with sensors to generate the map. This is a burdensome task for the operator. Thus, an exploration method in an unknown environment for autonomously generating a map has been studied for decades. The main method is frontier-based exploration [1] which performs autonomous exploration using local map information. The algorithm is useful approach for the mapping unknown environments, on the other hand, the method has the following problem for applying to mapping method in a wide environment like a factory; since the map information which is being gradually extended is used, the calculation cost increases in proportion to the time [2]. From this problem, when the calculation time of the map information becomes long, the exploring efficiency will be deteriorated. Thus, it takes the time to generate the map. For more efficient exploration, an autonomous exploration algorithm using only infrared sensor and odometry information of a robot is proposed as a sensor-based exploration approach without using map information. The proposed method requires only a depth sensor and camera for which the Kinect is used as the equipment and one mobile robot. Turtlebot2 with Kinect is used as a wheeled mobile robot, and the effectiveness of the proposed method will be confirmed by comparing with frontier-based exploration and proposed method by indoor experiments.
机译:本文对映射未知环境的自主探索算法。自动室内携带机器人需要一种地图作为工作空间的知识,以便有效地执行导航任务。 SLAM(同时定位和映射)被广泛用作发电地图。然而,该地图基于人类操作配备有传感器的机器人来生成地图的前提。这是操作员的繁重任务。因此,已经研究了几十年来自主生成地图的未知环境中的探索方法。主要方法是基于前沿的探索[1],使用本地地图信息执行自主探索。另一方面,该算法是映射未知环境的有用方法,另一方面,该方法具有以下问题,以便在诸如工厂的广泛环境中应用映射方法;由于使用正在逐渐扩展的地图信息,因此计算成本与时间比例增加[2]。从这个问题来看,当地图信息的计算时间变长时,探索效率会恶化。因此,需要生成地图时间。为了更有效的探索,建议仅使用机器人的红外传感器和机器人的内径信息的自主探索算法作为基于传感器的探测方法,而无需使用地图信息。所提出的方法仅需要一个深度传感器和照相机,其中Kinect用作设备和一个移动机器人。 Murtlebot2用Kinect用作轮式移动机器人,并且通过与室内实验的前沿探索和提出的方法相比,将确认所提出的方法的有效性。

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