Abstract
[Objective] By optimizing the sorting trajectory of Delta robots, while ensuring sorting accuracy, this paper aims to reduce comprehensive energy consumption, shorten operating time, and minimize operational impact. [Methods] Based on the analysis of automated food production lines, a trajectory optimization method for food sorting-oriented Delta robots was proposed, which combined 5-order non-uniform rational B-spline curves, multi-objective optimization, and multi-objective evolutionary algorithms based on decomposition. By taking comprehensive energy consumption, operating time, and operational impact as optimization objectives, an improved multi-objective evolutionary algorithm based on decomposition was used to solve and verify 5-order non-uniform rational B-spline curves. [Results] This method has improved the efficiency of the food production line (reducing operating time by 5. 00%), extended the service life of equipment (reducing operational impact by 17. 32%), and reduced food loss. [Conclusion] The combination of 5-order non-uniform rational B-spline curves and multi-objective optimization can effectively balance the high-speed and smooth operation of Delta robots.
Publication Date
11-19-2025
First Page
75
Last Page
82
DOI
10.13652/j.spjx.1003.5788.2025.60112
Recommended Citation
Hui, ZHU; Shufeng, ZHAO; Rucheng, LI; and Fei, LIU
(2025)
"Research on trajectory optimization of Delta robot in food production lines based on improved MOEA/D algorithm,"
Food and Machinery: Vol. 41:
Iss.
10, Article 11.
DOI: 10.13652/j.spjx.1003.5788.2025.60112
Available at:
https://www.ifoodmm.cn/journal/vol41/iss10/11
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