Coverage Path Planning Under the Energy Constraint
Coverage Path Planning Under the Energy Constraint
复制标题
DOI：
10.1109/icra.2018.8462867
复制
发表时间：
2018-05
期刊：
影响因子：
--
通讯作者：
Minghan Wei;Volkan Isler
中科院分区：
文献类型：
--
作者：
Minghan Wei;Volkan Isler
在覆盖路径规划问题中，一个常见的假设是机器人可以在不充电的情况下完全覆盖环境。然而，在现实中，大多数移动机器人系统都是在电池限制下运行的。为了考虑这一约束，我们考虑了当工作环境很大并且机器人需要多次充电才能完全覆盖环境时的问题。我们关注的是一个几何版本，其中环境被表示为带有单个充电站的多边形网格。整个环境的能源消耗被认为是均匀的，并与行驶的距离成正比。我们首先提出了一种用于轮廓连通环境的恒定因子逼近算法。然后，我们将该算法扩展到一般环境。我们还在空中机器人上进行的实验中验证了结果。
In the coverage path planning problem, a common assumption is that the robot can fully cover the environment without recharging. However, in reality most mobile robot systems operate under battery limitations. To incorporate this constraint, we consider the problem when the working environment is large and the robot needs to recharge multiple times to fully cover the environment. We focus on a geometric version where the environment is represented as a polygonal grid with a single charging station. Energy consumption throughout the environment is assumed to be uniform and proportional to the distance traveled. We first present a constant-factor approximation algorithm for contour-connected environments. We then extend the algorithm for general environments. We also validate the results in experiments performed with an aerial robot.