Abstract
[Objective] To address the path planning challenges for robots in the ground-pot areas of light-flavor Baijiu fermentation workshops. [Methods] A robotic path planning method, named C-EAFO-YBWC, is proposed. First, gamma correction and unsharp masking are used to enhance image quality, combined with the adaptive FAST threshold to improve ORB feature point extraction, ensuring the localization accuracy of the ORB-SLAM 2 algorithm under complex lighting. Second, BiFPN and Coordinate Attention (CA) mechanisms are integrated into YOLOv 10n and optimized with WIoU to detect fermentation pots and generate path points. Finally, by combining robot self-localization and ground-pot detection, the path points are transformed into the robot's coordinate system to guide its motion. [Results] In the four test sequences selected from the EuRoC dataset, the RMSE is reduced by 2.60%, 43.26%, 12.72%, and 30.10%, respectively. In tests using a ground-pot dataset, mAP@ 0.5 improves by 1.1 percentage points, while Params and FLOPs are reduced by 8.33% and 2.32%, respectively. [Conclusion] The proposed EAF_ORB-SLAM 2 and YOLOv 10n_BWC algorithms effectively ensure the validity of path planning.
Publication Date
1-13-2026
First Page
73
Last Page
81
DOI
10.13652/j.spjx.1003.5788.2025.80152
Recommended Citation
Shoujie, GUO; Jianyan, TIAN; Long, CHENG; and Sugang, WANG
(2026)
"Path planning method for robots in the ground-pot areas of fermentation workshops,"
Food and Machinery: Vol. 41:
Iss.
12, Article 10.
DOI: 10.13652/j.spjx.1003.5788.2025.80152
Available at:
https://www.ifoodmm.cn/journal/vol41/iss12/10
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