Enhancing the A Algorithm for Efficient Route Planning of Agriculture
The A* algorithm is wildly famous and is used in many areas, such as farming robots and global positioning system (GPS) systems, for effective route planning. Even though the algorithm has many benefits, it has some downsides, especially regarding how well it works and how long the paths are. This w...
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| Vydáno v: | International Workshop on Cellular Nanoscale Networks and their Applications s. 1 - 4 |
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| Hlavní autoři: | , , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
28.09.2023
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| Témata: | |
| ISSN: | 2165-0179 |
| On-line přístup: | Získat plný text |
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| Shrnutí: | The A* algorithm is wildly famous and is used in many areas, such as farming robots and global positioning system (GPS) systems, for effective route planning. Even though the algorithm has many benefits, it has some downsides, especially regarding how well it works and how long the paths are. This work explains how to improve the standard A* algorithm by changing it to get around these problems. The suggested method aims to improve how well the A* algorithm works by making changes that make route planning more effective and shorten the length of paths. When the modified algorithm was tested against the standard A* algorithm, the outcomes showed that the improved algorithm was much better. The new formula cuts the time it takes to plan a route by 11.11% and the total distance driven by 10.99% on average. These outcomes show how well the method described was at making the A* algorithm work better. The improved A* algorithm may help in many different areas. For example, in farming robotics, where route planning is critical, the improved method could help robots move faster and more efficiently, speeding up job finishing and making better use of resources. So, path planning is a significant part of industrial robots. In the same way, the better formula in GPS systems may give users route suggestions that are more accurate and efficient. |
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| ISSN: | 2165-0179 |
| DOI: | 10.1109/CNNA60945.2023.10652835 |