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Sensor planning with hierarchically distributed perception net

机译:具有分层分布感知网络的传感器规划

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A new paradigm of sensor planning is presented based on anhierarchically distributed perception net (HDPN) proposed as a generalnsensing architecture. The sensor planning is done by optimizing thenparameters as well as the structures of HDPN for the given sensing goalsndenoted respectively as parametric and structural sensor planning. Innthe proposed parametric sensor planning, the sensing parameters of HDPNnare iteratively modified so that HDPN ultimately generates the desirednaccuracy of outputs at a minimum sensing cost. The structural sensornplanning aims at self-organizing an optimal configuration of HDPN bynexploiting redundant sensing. A simulation study is conducted bynapplying the proposed parametric sensor planning method for the accuratenself-localization of a mobile robot operating in a known environmentnwith multiple range sensors. Simulation results verify the validity ofnthe proposed method. The proposed paradigm provides a formal, yetngeneral and efficient method of representing and solving a sensornplanning problem for an integrated sensor system
机译:提出了一种新的传感器计划范式,该模型基于提出的通用分布感知网络(HDPN)。通过针对给定的感测目标优化参数和HDPN的结构来完成传感器规划,分别表示为参数和结构传感器规划。在提出的参数传感器计划中,对HDPN的传感参数进行了迭代修改,以使HDPN最终以最小的传感成本产生所需的输出精度。结构传感器规划旨在通过利用冗余传感来自组织HDPN的最佳配置。通过将所提出的参数传感器计划方法应用于在已知环境中运行的具有多个范围传感器的移动机器人的精确自定位,进行了仿真研究。仿真结果验证了该方法的有效性。所提出的范例提供了一种形式化,通用而有效的方法来表示和解决集成传感器系统的传感器规划问题

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