Minimalist Robot Navigation and Coverage Using a Dynamical System Approach
Minimalist Robot Navigation and Coverage Using a Dynamical System Approach
复制标题
使用动力系统方法的极简机器人导航和覆盖
DOI：
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发表时间：
2017
期刊：
影响因子：
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通讯作者：
Dylan A. Shell
中科院分区：
文献类型：
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作者：
Tauhidul Alam;Leonardo Bobadilla;Dylan A. Shell
只要配备一个时钟和一个接触式传感器，移动机器人就可以通过编程以一种可预测的方式在墙上反弹：机器人向前行驶，直到遇到障碍物，然后原地旋转，再次向前行驶。虽然这种行为很容易建模和实现，但它有用吗？我们提出了一种使用这种弹跳机器人同时解决导航和覆盖问题的方法。前者需要找到从一个姿势到另一个姿势的路径，而后者则需要在期望的位置上组合不同的路径。我们的方法有以下步骤：1)使用简单的弹跳策略从环境几何构造一个有向图；2)在给定的一对初始姿态和目标姿态之间或所有可能的初始姿态和目标姿态对之间生成图上用于导航的最短路径；3)计算弹跳策略的最优分布，使实际覆盖分布尽可能接近目标覆盖分布。最后，我们给出了多个仿真和硬件实验的实验结果，以证明我们的方法的实用性。
Equipped only with a clock and a contact sensor, a mobile robot can be programmed to bounce off walls in a predictable way: the robot drives forward until meeting an obstacle, then rotates in place and proceeds forward again. Though this behavior is easily modeled and trivially implemented, is it useful?We present an approach for solving both navigation and coverage problems using such a bouncing robot. The former entails finding a path from one pose to another, while the latter combines different paths over desired locations. Our approach has the following steps: 1) A directed graph is constructed from the environment geometry using the simple bouncing policies, 2) The shortest path on the graph, for navigation, is generated between either one given pair of initial and goal poses or all possible pairs of initial and goal poses, 3) The optimal distribution of bouncing policies is computed so that the actual coverage distribution is as close as possible to the target coverage distribution. Finally, we present experimental results from multiple simulations and hardware experiments to demonstrate the practical utility of our approach.