Ergodic Exploration of Distributed Information
Ergodic Exploration of Distributed Information
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DOI：
10.1109/tro.2015.2500441
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发表时间：
2016-02-01
影响因子：
7.8
通讯作者：
Murphey, Todd D.
中科院分区：
文献类型：
--
作者：
Miller, Lauren M.;Silverman, Yonatan;Murphey, Todd D.
针对具有非线性测量和动力学特性的自主移动机器人，提出了一种主动搜索轨迹综合技术。该方法利用规划轨迹相对于期望信息密度图的遍历性，在搜索过程中闭合循环。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，都适合于关于期望信息密度的覆盖，从而在单一目标函数中的探索和开发之间进行权衡。作为演示，我们使用机器人电子定位平台来估计描述水下环境中静态目标的位置和大小参数。我们的结果表明，分布式信息遍历探索算法的性能优于常用的面向信息的控制器，特别是在存在干扰的情况下。
This paper presents an active search trajectory synthesis technique for autonomous mobile robots with nonlinear measurements and dynamics. The presented approach uses the ergodicity of a planned trajectory with respect to an expected information density map to close the loop during search. 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, thus trading off between exploration and exploitation in a single-objective function. As a demonstration, we use a robotic electrolocation platform to estimate location and size parameters describing static targets in an underwater environment. Our results demonstrate that the ergodic exploration of distributed information algorithm outperforms commonly used information-oriented controllers, particularly when distractions are present.