Talk Resource-Efficiently to Me: Optimal Communication Planning for Distributed Loop Closure Detection
Talk Resource-Efficiently to Me: Optimal Communication Planning for Distributed Loop Closure Detection
复制标题
与我高效地交谈：分布式环路闭合检测的最佳通信规划
DOI：
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复制
发表时间：
2017
期刊：
影响因子：
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通讯作者：
J. How
中科院分区：
文献类型：
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作者：
Matthew Giamou;Kasra Khosoussi;J. How
由于协同同时定位和地图绘制（CSLAM）的分布式性质，检测机器人间的环路闭合需要与其他机器人共享传感数据。天真的数据共享方法很容易导致关键任务资源的浪费。本文研究了CLAM的后勤方面。特别是，我们提出了一个通用的资源有效的通信规划框架，考虑到交换的数据总量和参与机器人之间的劳动分工。与其他最先进的方法相比，我们的框架能够验证同一组潜在的机器人间循环关闭，同时交换的数据少得多，并影响诱导的工作负载。我们开发了一个快速算法，找到全局最优的通信策略，并提出理论分析，以表征必要和充分条件下，简单的策略是最佳的。建议的框架进行了广泛的评估，从KITTI里程计基准数据集的数据。
Due to the distributed nature of cooperative simultaneous localization and mapping (CSLAM), detecting inter-robot loop closures necessitates sharing sensory data with other robots. A naïve approach to data sharing can easily lead to a waste of mission-critical resources. This paper investigates the logistical aspects of CSLAM. Particularly, we present a general resource-efficient communication planning framework that takes into account both the total amount of exchanged data and the induced division of labor between the participating robots. Compared to other state-of-the-art approaches, our framework is able to verify the same set of potential inter-robot loop closures while exchanging considerably less data and influencing the induced workloads. We develop a fast algorithm for finding globally optimal communication policies, and present theoretical analysis to characterize the necessary and sufficient conditions under which simpler strategies are optimal. The proposed framework is extensively evaluated with data from the KITTI odometry benchmark datasets.
影响因子：
9.2
作者：
Geiger, A.;Lenz, P.;Urtasun, R.
通讯作者：
Urtasun, R.