Optimizing autonomous navigation algorithm Î¼ a comparative study of new and legacy approach

J. Rakun; G. PopiÄ

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Optimizing autonomous navigation algorithm Î¼ a comparative study of new and legacy approach

In: Precision agriculture '25

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J. Rakun

J. Rakun jurij.rakun@um.si

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G. PopiÄ

G. PopiÄ
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Type:: Chapter

Pages:: 956â961

DOI:: https://doi.org/10.1163/9789004725232_125

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Dar Hadith al Hassania

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This paper presents a new algorithm for the autonomous navigation of field robots, optimized for faster and more accurate performance in agricultural environments. The primary objective was to improve upon an existing algorithm by enhancing its navigation accuracy, reducing the number of damaged crops, and achieving faster execution times. The new algorithm incorporates advanced data filtering techniques and a utilization of sensor data, using LiDAR and IMU sensors to generate a 3D point cloud for precise navigation through structured crop rows. Both algorithms were tested and compared in simulation and real-world environments, using the FarmBeast robotic platform. The results demonstrate that the new algorithm achieves up to a 33% reduction in time on certain field sections and minimizes crop damage by 25%.

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Precision agriculture '25

E-Book ISBN:: 9789004725232

Publisher:: Wageningen Academic

Print Publication Date:: 18 Jun 2025

Subjects
- Life Sciences
  - General
  - Agriculture & Environment

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Optimizing autonomous navigation algorithm Î¼ a comparative study of new and legacy approach

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Precision agriculture '25

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