Back to Search Start Over

An Adaptive and Automatic Power Supply Distribution System with Active Landmarks for Autonomous Mobile Robots

Authors :
Zhen Li
Yuliang Gao
Miaomiao Zhu
Haonan Tang
Lifeng Zhang
Source :
Sensors, Vol 24, Iss 18, p 6152 (2024)
Publication Year :
2024
Publisher :
MDPI AG, 2024.

Abstract

With the development of automation and intelligent technologies, the demand for autonomous mobile robots in the industry has surged to alleviate labor-intensive tasks and mitigate labor shortages. However, conventional industrial mobile robots’ route-tracking algorithms typically rely on passive markers, leading to issues such as inflexibility in changing routes and high deployment costs. To address these challenges, this study proposes a novel approach utilizing active landmarks—battery-powered luminous landmarks that enable robots to recognize and adapt to flexible navigation requirements. However, the reliance on batteries necessitates frequent recharging, prompting the development of an automatic power supply system. This system integrates omnidirectional contact electrodes on mobile robots, allowing to recharge active landmarks without precise positional alignment. Despite these advancements, challenges such as the large size of electrodes and non-adaptive battery charging across landmarks persist, affecting system efficiency. To mitigate these issues, this research focuses on miniaturizing active landmarks and optimizing power distribution among landmarks. The experimental results of this study demonstrated the effectiveness of our automatic power supply method and the high accuracy of landmark detection. Our power distribution calculation method can adaptively manage energy distribution, improving the system’s persistence by nearly three times. This study aims to enhance the practicality and efficiency of mobile robot remote control systems utilizing active landmarks by simplifying installation processes and extending operational durations with adaptive and automatic power supply distribution.

Details

Language :
English
ISSN :
14248220
Volume :
24
Issue :
18
Database :
Directory of Open Access Journals
Journal :
Sensors
Publication Type :
Academic Journal
Accession number :
edsdoj.24e3e96aaf204481b97635af6d497bce
Document Type :
article
Full Text :
https://doi.org/10.3390/s24186152