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首页> 外文期刊>Discrete Applied Mathematics >Optimal online and offline algorithms for robot-assisted restoration of barrier coverage
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Optimal online and offline algorithms for robot-assisted restoration of barrier coverage

机译:最佳的在线和离线算法,用于机器人辅助障碍覆盖

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Assume that n wireless sensors are initially arbitrarily distributed on a line segment barrier. Each sensor is said to cover the portion of the barrier that intersects with its sensing area. Owing to incorrect initial position, or the death of some of the sensors, the barrier is not completely covered by the sensors. We employ a mobile robot to move the sensors to final positions on the barrier such that barrier coverage is guaranteed. We seek algorithms that minimize the length of the robot's trajectory, since this allows the restoration of barrier coverage as soon as possible. We give an optimal linear-time offline algorithm that gives a minimum-length trajectory for a robot that starts at one end of the barrier and achieves the restoration of barrier coverage. We also study two different online models: one in which the online robot does not know the length of the barrier in advance, and the other in which the online robot knows the length of the barrier. For the case when the online robot does not know the length of the barrier, we prove a tight bound of 3/2 on the competitive ratio, and we give a tight lower bound of 5/4 on the competitive ratio in the other case. (C) 2020 Elsevier B.V. All rights reserved.
机译:假设N无线传感器最初在线段屏障上任意分布。据说每个传感器覆盖与其传感区域相交的屏障的一部分。由于初始位置不正确,或某些传感器的死亡,传感器没有完全覆盖屏障。我们采用移动机器人将传感器移动到屏障上的最终位置,使得保证屏障覆盖范围。我们寻求最小化机器人轨迹的长度的算法,因为这允许尽快恢复屏障覆盖。我们提供了一个最佳的线性时间离线算法,其为机器人提供最小长度的轨迹,该机器人在屏障的一端开始,并且实现了障碍覆盖的恢复。我们还研究了两种不同的在线模型:在线机器人预先不知道屏障长度的不同在线模型,另一个在线机器人知道屏障的长度。对于在线机器人不知道屏障长度的情况下,我们证明了竞争比率的3/2的紧张界限,我们在其他情况下竞争比率紧密下限为5/4。 (c)2020 Elsevier B.V.保留所有权利。

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