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.
|Original language||English (US)|
|Title of host publication||2018 IEEE International Conference on Robotics and Automation, ICRA 2018|
|Publisher||Institute of Electrical and Electronics Engineers Inc.|
|Number of pages||6|
|State||Published - Sep 10 2018|
|Event||2018 IEEE International Conference on Robotics and Automation, ICRA 2018 - Brisbane, Australia|
Duration: May 21 2018 → May 25 2018
|Name||Proceedings - IEEE International Conference on Robotics and Automation|
|Conference||2018 IEEE International Conference on Robotics and Automation, ICRA 2018|
|Period||5/21/18 → 5/25/18|
Bibliographical noteFunding Information:
This work is supported in part by NSF Award # 1525045, a MnDrive RSAM Industrial Partnership grant with The Toro Company and a grant from Minnesota State LCCMR Program.
© 2018 IEEE.