Issue |
BIO Web Conf.
Volume 130, 2024
International Scientific Conference on Biotechnology and Food Technology (BFT-2024)
|
|
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Article Number | 08031 | |
Number of page(s) | 11 | |
Section | Food and Agriculture Organization | |
DOI | https://doi.org/10.1051/bioconf/202413008031 | |
Published online | 09 October 2024 |
Mivar-based route planning simulation model for obstacle-aware autonomous agricultural machinery
Bauman Moscow State Technical University, 2-ya Baumanskaya Street, 5/1, Moscow, 105005, Russian Federation
* Corresponding author: ovarlamov@gmail.com
Autonomous robot navigation is increasingly becoming an important task that requires solutions. This paper explores the practical application of logical artificial intelligence to address the problem of route planning, using the example of a computer game. Within the scope of this work, a knowledge base model was created, and a new version of the mivar reasoner was developed for integration with Unity. This reasoner allows the activation of logical rules with linear complexity. As a result, a system was developed that processes user input for position and moves an autonomous agent in a virtual environment according to the rules. This work confirms the feasibility of using mivar technologies to improve control systems of autonomous robots in the area of agriculture. The study also emphasizes the adaptability of mivar networks in dynamic environments, demonstrating their ability to effectively process changes in real-time. This research shows enhanced decision-making capabilities and reliable navigation strategies for autonomous agents, setting a precedent for future developments in autonomous digital solutions for agriculture. The results obtained open new prospects for the advancement of technologies in the field of autonomous navigation.
© The Authors, published by EDP Sciences, 2024
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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