Optimal planning for target localization and coverage using range sensing
Optimal planning for target localization and coverage using range sensing
复制标题
使用距离感测对目标定位和覆盖范围进行优化规划
DOI：
10.1109/coase.2015.7294129
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发表时间：
2015
期刊：
影响因子：
--
通讯作者：
T. Murphey
中科院分区：
文献类型：
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作者：
Lauren M. Miller;T. Murphey
提出了一种应用于距离感知的主动感知策略自主计算算法。我们使用的退层算法，称为分布式信息的遍历探索（EEDI），包括两个主要组成部分：a)基于先验信息和传感器模型计算搜索空间上的期望信息密度图，b)相对于该信息图，在传感器配置空间上进行遍历轨迹优化。遍历控制算法不依赖于搜索或动作空间的离散化，并且无论信息是扩散的还是局部的，都能很好地覆盖预期的信息密度。我们使用固定位置距离传感器在不同噪声水平下模拟二维工作空间中目标的成功定位和识别，并将性能与信息最大化策略进行比较。
This paper presents an algorithm for autonomously calculating active sensing strategies applied to range sensing. The receding-horizon algorithm we use, called Ergodic Exploration of Distributed Information (EEDI), involves two major components: a) calculation of an expected information density map over the search space based on prior information and a model of the sensor, and b) ergodic trajectory optimization over the sensor configuration space with respect to that information map. The ergodic control algorithm does not rely on discretization of the search or action spaces, and is well-posed for coverage with respect to the expected information density whether the information is diffuse or localized. We simulate successful localization and discrimination of targets in a two-dimensional workspace using a fixed-location range sensor under various noise levels, and compare performance to an information maximizing strategy.