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Bi-objective data gathering path planning for vehicles with bounded curvature

机译:有界曲率车辆的双目标数据收集路径规划

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A Wireless Sensor Network consists of several simple sensor nodes deployed in an environment having as primary goal data acquisition. However, due to limited sensor communication range, oftentimes it is necessary to use a mobile sink node that will visit sensor nodes to gather up their collected data. An important aspect that must be taken into account in this case are the intrinsic limitations of the vehicle used, such as kinematic and dynamic constraints, since most of the vehicles present in our everyday life have such restrictions. Therefore, this work addresses the problem of planning efficient paths, which are length and time of collection optimized for data gathering by a mobile robot with bounded curvature. We propose the use of the classical NSGA-II in order to tackle both objective functions. The methodology was evaluated through several experiments in a simulated environment. The results outperform the classical evolutionary approach to the single-objective problem specially considering the trade-off between overall length and collecting time. (C) 2016 Elsevier Ltd. All rights reserved.
机译:无线传感器网络由几个简单的传感器节点组成,这些节点部署在具有主要目标数据采集功能的环境中。但是,由于传感器通信范围有限,因此经常需要使用移动接收器节点,该节点将访问传感器节点以收集其收集的数据。在这种情况下,必须考虑的重要方面是所用车辆的固有局限性,例如运动学和动态约束,因为我们日常生活中存在的大多数车辆都具有这种局限性。因此,这项工作解决了规划有效路径的问题,该路径是针对具有有限曲率的移动机器人优化的数据收集长度和时间。我们建议使用经典的NSGA-II来解决这两个目标功能。该方法通过在模拟环境中进行的几次实验进行了评估。考虑到总长度和收集时间之间的权衡,结果优于传统的单目标问题进化方法。 (C)2016 Elsevier Ltd.保留所有权利。

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