Cooperative Search of Multiple Unknown Transient Radio Sources Using Multiple Paired Mobile Robots
Cooperative Search of Multiple Unknown Transient Radio Sources Using Multiple Paired Mobile Robots
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DOI：
10.1109/tro.2014.2333097
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发表时间：
2014-07
影响因子：
7.8
通讯作者：
Chang-Young Kim;Dezhen Song;Yiliang Xu;J. Yi;Xinyu Wu
中科院分区：
文献类型：
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作者：
Chang-Young Kim;Dezhen Song;Yiliang Xu;J. Yi;Xinyu Wu
我们开发了一种本地化方法，以使一个移动机器人团队可以搜索多个未知的瞬态无线电源。由于信号源匿名，短传输持续时间和动态传输模式，机器人无法将无线电源视为连续无线电信标。此外，机器人不知道源传输功率，并且传感范围有限。为了应对这些挑战，我们将机器人配对，并使用配对机器人的信号强度比开发合作传感模型。我们正式证明，可以通过组合成对的关节后验概率来获得M-ROBOT团队源位置的联合条件后验概率，这可以从信号强度比中得出。此外，我们提出了一个成对的脊行走算法（PRWA），以基于高概率区域的聚类和当地香农熵的最小化来协调机器人对。我们已经在硬件驱动的仿真和物理实验下实施并验证了该算法。实验结果表明，基于PRWA的本地化方案始终优于其他四种启发式方法。
We develop a localization method to enable a team of mobile robots to search for multiple unknown transient radio sources. Because of signal source anonymity, short transmission durations, and dynamic transmission patterns, robots cannot treat the radio sources as continuous radio beacons. Moreover, robots do not know the source transmission power and have limited sensing ranges. To cope with these challenges, we pair up robots and develop a cooperative sensing model using signal strength ratios from the paired robots. We formally prove that the joint conditional posterior probability of source locations for the m-robot team can be obtained by combining the pairwise joint posterior probabilities, which can be derived from signal strength ratios. Moreover, we propose a pairwise ridge walking algorithm (PRWA) to coordinate the robot pairs based on the clustering of high-probability regions and the minimization of local Shannon entropy. We have implemented and validated the algorithm under both the hardware-driven simulation and physical experiments. Experimental results show that the PRWA-based localization scheme consistently outperforms the other four heuristics.