On mutual information-based control of range sensing robots for mapping applications
On mutual information-based control of range sensing robots for mapping applications
复制标题
DOI：
10.1177/0278364914526288
复制
发表时间：
2014-09-01
影响因子：
9.2
通讯作者：
Rus, Daniela
中科院分区：
文献类型：
--
作者：
Julian, Brian J.;Karaman, Sertac;Rus, Daniela
在本文中，我们研究的信息内容和空间实现的范围测量的测绘机器人之间的相关性。要做到这一点，我们考虑的任务，构建一个二进制贝叶斯过滤器的占用网格地图。使用基于光束的传感器模型（相对于加性白色高斯噪声模型），我们证明了任何控制器的任务，以最大限度地提高互信息奖励函数最终吸引到未探索的空间。这种直观的行为完全来自于占用网格映射算法的几何依赖性和互信息的单调性。由于它依赖于机器人的位置和周围细胞的不确定性，互信息编码的几何关系，是机器人控制的基础，从而产生几何相关的奖励表面上的机器人可以导航。我们还提供了一个算法实现计算互信息，并表明其最坏情况下的时间和空间的复杂性是二次和线性的，分别相对于地图的空间分辨率。最后，我们提出的实验结果，采用全向地面机器人配备了激光测距仪。我们的实验结果支持我们的理论和计算结果。
In this paper we examine the correlation between the information content and the spatial realization of range measurements taken by a mapping robot. To do so, we consider the task of constructing an occupancy grid map with a binary Bayesian filter. Using a beam-based sensor model (versus an additive white Gaussian noise model), we prove that any controller tasked to maximize a mutual information reward function is eventually attracted to unexplored space. This intuitive behavior is derived solely from the geometric dependencies of the occupancy grid mapping algorithm and the monotonic properties of mutual information. Since it is dependent on both the robot's position and the uncertainty of the surrounding cells, mutual information encodes geometric relationships that are fundamental to robot control, thus yielding geometrically relevant reward surfaces on which the robot can navigate. We also provide an algorithmic implementation for computing mutual information and show that its worst-case time and space complexities are quadratic and linear, respectively, with respect to the map's spatial resolution. Lastly, we present the results of experiments employing an omnidirectional ground robot equipped with a laser range finder. Our experimental results support our theoretical and computational findings.