Abstract
[Objective] Aiming at the limitations of low operating efficiency, high energy consumption, and poor stability in traditional trajectory planning of Delta robots during food sorting, this study proposes an optimized trajectory scheme to effectively reduce operation time, lower energy consumption, and improve operation stability. [Methods] On the basis of the architecture of the food sorting system, a trajectory optimization method for the Delta robot is proposed, which combines quintic uniform B-spline curves with multi-objective optimization. Firstly, the trajectory is planned using quintic uniform B-spline curves to minimize motion impact. Subsequently, a multi-objective optimization model integrating time, energy consumption and stability is constructed. This model is solved using an improved multi-objective particle swarm optimization algorithm, which incorporates adaptive weight adjustment and crowding ranking optimization, to obtain the optimal trajectory parameters. Finally, an experimental platform is constructed to verify the effectiveness of the proposed method. [Results] Compared with conventional methods, the experimental method reduces robot operation time by over 9.50%, decreases energy consumption by over 9.00%, and improves stability by over 18.00%. Meanwhile, it maintains an actual sorting accuracy above 97.50%, with an average sorting time of less than 0.80 seconds. [Conclusion] The proposed method achieves multi-objective collaborative optimization of operation time, energy consumption, and stability, effectively improving the operation performance and stability of Delta robots in food sorting scenarios.
Publication Date
4-3-2026
First Page
100
Last Page
108
DOI
10.13652/j.spjx.1003.5788.2025.60156
Recommended Citation
Min, LIU; Pengfei, WU; and Xiao, WANG
(2026)
"Multi-objective optimization of food sorting robot trajectory based on improved uniform B-spline,"
Food and Machinery: Vol. 42:
Iss.
2, Article 12.
DOI: 10.13652/j.spjx.1003.5788.2025.60156
Available at:
https://www.ifoodmm.cn/journal/vol42/iss2/12
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