Story validation and approximate path inference with a sparse network of heterogeneous sensors
Story validation and approximate path inference with a sparse network of heterogeneous sensors
复制标题
使用异构传感器的稀疏网络进行故事验证和近似路径推理
DOI：
10.1109/icra.2011.5979827
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发表时间：
2011
期刊：
影响因子：
--
通讯作者：
S. LaValle
中科院分区：
文献类型：
--
作者：
Jingjin Yu;S. LaValle
给定一个智能体的故事（机器人的传感器输出或人类讲述的故事）和来自异构传感器备用网络的记录，本文提供了有效的算法来验证是否有可能重建一条与传感器记录兼容的路径，该路径也“接近”智能体的故事。在解决所提出的问题时，我们表明，有效地利用一个独特的有限自动机结构，在故事的长度和传感器观测历史的长度上产生线性的时间复杂度。除了直接适用于安全和取证问题之外，使用外部传感器的行为验证的想法在补充设计时模型验证方面也很有希望。
Given a story from an agent (sensor outputs from a robot or a tale told by a human) and recordings from a spare network of heterogeneous sensors, this paper provides efficient algorithms that validate whether it is possible to reconstruct a path compatible with the sensor recordings that is also “close” to the agent's story. In solving the proposed problems, we show that effective exploitation of a unique finite automaton structure yields time complexity linear in both the length of the story and the length of the sensor observation history. Besides immediate applicability towards security and forensics problems, the idea of behavior validation using external sensors also appears promising in complementing design time model verification.