Robot Memorial Path Planning for Smart Access of Indoor Distributed Charging Piles

2Citations
Citations of this article
14Readers
Mendeley users who have this article in their library.

This article is free to access.

Abstract

Autonomous mobile service robots are used to complete many tasks, such as cleaning, transporting goods and monitoring. Such tasks usually require uninterrupted and continuous service. However, the battery of the robot is limited and must be charged frequently. For a large number of robots, it is essential to select a suitable charging pile. For this issue, we propose a path planning model for robots to intelligently access a limited number of charging piles distributed on the map. The traditional path planning model mainly considers the shortest path criterion to generate the path. Different from this, the path planning model in this paper not only considers the shortest path, but also the service position of the robot after charging, the remaining power of the robot, the state of the charging pile and the position of the robot in the map. Our path planning assigns the most suitable charging pile to the robot that needs charging. To solve the problem of high memory consumption and slow search speed when traditional A∗ algorithm is used for path planning, we propose local memorial path planning (LMPP) algorithm to quickly generate effective paths. The simulation results show that the proposed robot charging path planner can improve the robot service satisfaction and plan the effective path to the available charging piles.

Cite

CITATION STYLE

APA

Deng, Y., Li, T., Xie, M., & Chen, W. (2023). Robot Memorial Path Planning for Smart Access of Indoor Distributed Charging Piles. IEEE Access, 11, 27893–27918. https://doi.org/10.1109/ACCESS.2023.3257570

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free