论文标题
结合多机器人探索的几何和信息理论方法
Combining Geometric and Information-Theoretic Approaches for Multi-Robot Exploration
论文作者
论文摘要
我们提出了一种使用$ P $机器人的团队来探索正交多边形的算法。该算法结合了信息理论探索算法和基于计算几何探索算法的思想。我们表明，相对于离线最佳探索算法，我们算法的探索时间具有竞争性（作为$ p $的函数）。该算法基于单重子探索算法，一种用于更高级别计划的树探索算法以及用于较低级别计划的suppodular定向急救算法。我们讨论如何将这种策略适应现实世界中的设置来处理嘈杂的传感器。除了理论分析外，我们还通过模拟多个机器人和单个机器人实验来研究算法的性能。
We present an algorithm to explore an orthogonal polygon using a team of $p$ robots. This algorithm combines ideas from information-theoretic exploration algorithms and computational geometry based exploration algorithms. We show that the exploration time of our algorithm is competitive (as a function of $p$) with respect to the offline optimal exploration algorithm. The algorithm is based on a single-robot polygon exploration algorithm, a tree exploration algorithm for higher level planning and a submodular orienteering algorithm for lower level planning. We discuss how this strategy can be adapted to real-world settings to deal with noisy sensors. In addition to theoretical analysis, we investigate the performance of our algorithm through simulations for multiple robots and experiments with a single robot.
