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A New Space and Time Sensor Fusion Method for Mobile Robot Navigation

机译:移动机器人导航的时空传感器融合新方法

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To fully utilize the information from the sensors of mobile robot, this paper proposes a new sensor-fusion technique where the sample data set obtained at a previous instant is properly transformed and fused with the current data sets to produce a reliable estimate for navigation control. Exploration of an unknown environment is an important task for the new generation of mobile service robots. The mobile robots may navigate by means of a number of monitoring systems such as the sonar-sensing system or the visual-sensing system. Notice that in the conventional fusion schemes, the measurement is dependent on the current data sets only. Therefore, more sensors are required to measure a given physical parameter or to improve the reliability of the measurement. However, in this approach, instead of adding more sensors to the system, the temporal sequences of the data sets are stored and utilized for the purpose. The basic principle is illustrated by examples and the effectiveness is proved through simulations and experiments. The newly proposed STSF (space and time sensor fusion) scheme is applied to the navigation of a mobile robot in an environment using landmarks, and the experimental results demonstrate the effective performance of the system.
机译:为了充分利用来自移动机器人传感器的信息,本文提出了一种新的传感器融合技术,其中将在前一瞬间获得的样本数据集正确转换并与当前数据集融合,以生成可靠的导航控制估计。探索未知环境是新一代移动服务机器人的一项重要任务。移动机器人可以借助于诸如声纳感测系统或视觉感测系统的多个监视系统来导航。请注意,在常规融合方案中,测量仅取决于当前数据集。因此,需要更多的传感器来测量给定的物理参数或提高测量的可靠性。但是,在这种方法中,不是将更多的传感器添加到系统中,而是将数据集的时间序列存储并用于此目的。通过实例说明了基本原理,并通过仿真和实验证明了其有效性。将新提出的STSF(时空传感器融合)方案应用于使用地标的环境中移动机器人的导航,实验结果证明了该系统的有效性能。

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