...
首页> 外文期刊>Computer networks >Coverage on demand: A simple motion control algorithm for autonomous robotic sensor networks
【24h】

Coverage on demand: A simple motion control algorithm for autonomous robotic sensor networks

机译:按需覆盖:用于自主机器人传感器网络的简单运动控制算法

获取原文
获取原文并翻译 | 示例

摘要

Autonomous robotic sensor networks are composed by robotic sensors that can move, sense and communicate with each other in a cooperative way, and therefore are more powerful than static sensor networks. In robotic sensor networks, an important problem is motion control: how each sensor can autonomously move to the desirable location for better network coverage over targets. In this paper, we study a new motion control problem that has the following critical requirements: (i) All targets in the area of interest should be covered by sensors; (ii) The number of sensors that cover one target depends on the target's importance, i.e., more important targets should be covered by more sensors; (iii) The robotic sensors are kept connected, i.e., each sensor has at least one route to any other sensor in the network; (iv) Proper distance between every two neighboring sensors is maintained to avoid coverage overlap and possible collision. As a solution to this problem, we propose a simple motion control algorithm that operates in a pure autonomous manner. The proposed algorithm models the coverage demand into virtual force field, and hence each sensor can simply obey the effect of force field onto it to move. We demonstrate by extensive simulations that the proposed algorithm is very effective and is applicable to large-scale networks. (C) 2018 Elsevier B.V. All rights reserved.
机译:自主机器人传感器网络由机器人传感器组成,它们可以以协作的方式相互移动,感应和通信,因此比静态传感器网络功能更强大。在机器人传感器网络中,一个重要的问题是运动控制:每个传感器如何自主地移动到所需的位置,以更好地覆盖目标网络。在本文中,我们研究了一个新的运动控制问题,它具有以下关键要求:(i)感兴趣区域中的所有目标都应被传感器覆盖; (ii)覆盖一个目标的传感器数量取决于目标的重要性,即,更重要的目标应被更多的传感器覆盖; (iii)机器人传感器保持连接状态,即每个传感器至少有一条通往网络中其他传感器的路由; (iv)保持每两个相邻传感器之间的适当距离,以避免覆盖范围重叠和可能的碰撞。作为此问题的解决方案,我们提出了一种以纯自主方式运行的简单运动控制算法。所提出的算法将覆盖需求建模为虚拟力场,因此每个传感器都可以简单地服从力场对其移动的影响。通过广泛的仿真,我们证明了所提出的算法非常有效,适用于大规模网络。 (C)2018 Elsevier B.V.保留所有权利。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号