无定位服务无线传感器网络中移动传感器的可靠导航

Qingjun Xiao, Bin Xiao, Jiaqing Luo, Guobin Liu
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引用次数: 10

摘要

本文讨论的问题是如何引导移动传感器(或机器人)跨越静态传感器覆盖的区域到达一种现象。提出了一种分布式、可靠、节能的移动机器人平滑运动轨迹构造算法。该方法首先在静态传感器之间构建一个基于分布式跳数的人工势场(DH-APF),该势场在现象附近只有一个局部最小值,然后利用引力沿着所构建的场的反向梯度将机器人导航到该最小值。除了对该现象的吸引力外,我们的算法还利用机器人携带的快速传感装置,采用额外的排斥力将机器人推离障碍物。与以往引导机器人沿着规划路径的导航算法相比,我们的算法可以(1)容忍偏离规划路径的潜在偏差,因为DH-APF覆盖了整个部署区域;(2)缓解弹道振荡问题;(3)避免与障碍物的潜在碰撞;(4)通过配置大的移动步长来节省静态传感器的宝贵能量,这对于忽略导航可靠性问题的算法来说是不可能的。我们对上述特征的理论分析考虑了实际的传感器网络问题,包括无线电不规则,数据包丢失和无线电冲突。我们在TinyOS上实现了所提出的算法,并在TOSSIM和python提供的高保真度仿真平台上测试了其性能。仿真结果验证了所提出的移动传感器导航算法的可靠性和高能效。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reliable navigation of mobile sensors in wireless sensor networks without localization service
This paper deals with the problem of guiding mobile sensors (or robots) to a phenomenon across a region covered by static sensors. We present a distributed, reliable and energy-efficient algorithm to construct a smoothed moving trajectory for a mobile robot. The reliable trajectory is realized by first constructing among static sensors a distributed hop count based artificial potential field (DH-APF) with only one local minimum near the phenomenon, and then navigating the robot to that minimum by an attractive force following the reversed gradient of the constructed field. Besides the attractive force towards the phenomenon, our algorithm adopts an additional repulsive force to push the robot away from obstacles, exploiting the fast sensing devices carried by the robot. Compared with previous navigation algorithms that guide the robot along a planned path, our algorithm can (1) tolerate the potential deviation from a planned path, since the DH-APF covers the entire deployment region; (2) mitigate the trajectory oscillation problem; (3) avoid the potential collision with obstacles; (4) save the precious energy of static sensors by configuring a large moving step size, which is not possible for algorithms neglecting the issue of navigation reliability. Our theoretical analysis of the above features considers practical sensor network issues including radio irregularity, packet loss and radio conflict. We implement the proposed algorithm over TinyOS and test its performance on the simulation platform with a high fidelity provided by TOSSIM and Tython. Simulation results verify the reliability and energy efficiency of the proposed mobile sensor navigation algorithm.
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