2 research outputs found
A Constant-Factor Approximation Algorithm for Online Coverage Path Planning with Energy Constraint
In this paper, we study the problem of coverage planning by a mobile robot
with a limited energy budget. The objective of the robot is to cover every
point in the environment while minimizing the traveled path length. The
environment is initially unknown to the robot. Therefore, it needs to avoid the
obstacles in the environment on-the-fly during the exploration. As the robot
has a specific energy budget, it might not be able to cover the complete
environment in one traversal. Instead, it will need to visit a static charging
station periodically in order to recharge its energy. To solve the stated
problem, we propose a budgeted depth-first search (DFS)-based exploration
strategy that helps the robot to cover any unknown planar environment while
bounding the maximum path length to a constant-factor of the shortest-possible
path length. Our -approximation guarantee advances the state-of-the-art
of log-approximation for this problem. Simulation results show that our
proposed algorithm outperforms the current state-of-the-art algorithm both in
terms of the traveled path length and run time in all the tested environments
with concave and convex obstacles
A Log-Approximation for Coverage Path Planning with the Energy Constraint
We consider the problem of covering an environment with a robot when the robot has limited energy budget. The environment is represented as a polygon with a grid, whose resolution is proportional to the robot size, imposed on it. There is a single charging station in the environment. At each time step, the robot can move from one grid cell to an adjacent one.The energy consumption when moving in the environment is assumed to be uniform and proportional to the distance traveled. Our goal is to minimize both the total distance and the number of visits to the charging station. We present a coverage path planning algorithm which has O(ln D) approxima-tion factor for both objectives, where D is the distance of thefurthest cell in the environment measured on the grid