LSMCL: Long-term Static Mapping and Cloning Localization for autonomous robot navigation using 3D LiDAR in dynamic environments

Lee, Yu-Cheol

doi:10.1016/j.eswa.2023.122688

Expert Systems with Applications

2024

DOI: 10.1016/j.eswa.2023.122688

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LSMCL: Long-term Static Mapping and Cloning Localization for autonomous robot navigation using 3D LiDAR in dynamic environments

Yu-Cheol Lee

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2024

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Cited by 2 publications

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Optimized TD3 algorithm for robust autonomous navigation in crowded and dynamic human-interaction environments

Neamah,

Mayorga Mayorga

2024

Results in Engineering

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Optimized TD3 algorithm for robust autonomous navigation in crowded and dynamic human-interaction environments

Neamah,

Mayorga Mayorga

2024

Results in Engineering

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

Li,

Gao,

Zhu

et al. 2024

Sensors

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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.

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LSMCL: Long-term Static Mapping and Cloning Localization for autonomous robot navigation using 3D LiDAR in dynamic environments

Cited by 2 publications

References 50 publications

Optimized TD3 algorithm for robust autonomous navigation in crowded and dynamic human-interaction environments

Optimized TD3 algorithm for robust autonomous navigation in crowded and dynamic human-interaction environments

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

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