<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>Several algorithms such as A*, Dijkstra, SLAM (Simultaneous Localisation and Mapping) and APF (Artificial Potential Field) were used in this study to create local maps, plan the shortest path, and localize mobile robots. In fact, when compared to the SLAM/APF method, these algorithms achieved a reduction in road length by 1.18 meters. Nevertheless, the SLAM/APF method outperformed the Dijkstra algorithm by reducing navigation time by 7.62 seconds and surpassed the A* method by reducing navigation time by 5.76 seconds.</p>
</abstract>

Several algorithms such as A*, Dijkstra, SLAM (Simultaneous Localisation and Mapping) and APF (Artificial Potential Field) were used in this study to create local maps, plan the shortest path, and localize mobile robots. In fact, when compared to the SLAM/APF method, these algorithms achieved a reduction in road length by 1.18 meters. Nevertheless, the SLAM/APF method outperformed the Dijkstra algorithm by reducing navigation time by 7.62 seconds and surpassed the A* method by reducing navigation time by 5.76 seconds.

Increasing the Efficiency of Mobile Robot Navigation Using Slam with Several Advanced Algorithms and Filters

Faculty of Mechanical Engineering, University of Prishtina

Strojnícky časopis - Journal of Mechanical Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Several algorithms such as A*, Dijkstra, SLAM (Simultaneous Localisation and Mapping) and APF (Artificial Potential Field) were used in this study to create...

Increasing the Efficiency of Mobile Robot Navigation Using Slam with Several Advanced Algorithms and Filters

Pubblicato online: 01 giu 2024

Pagine: 103 - 114

DOI: https://doi.org/10.2478/scjme-2024-0011

Parole chiave
SAM, A*, Dijkstra, Algorithm, Turtlebot2i

© 2024 Arbnor Pajaziti et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Increasing the Efficiency of Mobile Robot Navigation Using Slam with Several Advanced Algorithms and Filters

Pubblicato online: 01 giu 2024

Pagine: 103 - 114

DOI: https://doi.org/10.2478/scjme-2024-0011

Parole chiaveSAM, A*, Dijkstra, Algorithm, Turtlebot2i

© 2024 Arbnor Pajaziti et al., published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Parole chiave
SAM, A*, Dijkstra, Algorithm, Turtlebot2i