Customized Flat Paper Pallet Picking Path Planning of Intelligent Forklift Based on GPOPS

A flat paper pallet picking path planning approach is proposed in this paper to deal with the operation of forklift in confined working space. The constraints between the confined working space and the forklift position are constructed from the area relations. The path planning problem is divided into three stages and the linear velocity, angle of the forklift and position in the three different stages have corresponding constraints, respectively. Then, the pallet picking path planning problem is transformed into an optimal control problem. GPOPS is used to solve the nonlinear optimization problem and an effective forward and backward path planning method is proposed. The simulation illustrate the effectiveness of the proposed path planning method.

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Publication Details

Published
2025-03-21
DOI
https://doi.org/10.1109/icaace65325.2025.11019968
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.00

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Customized Flat Paper Pallet Picking Path Planning of Intelligent Forklift Based on GPOPS

Yongfei Xiao, Yang Zhang, Na Li, Zehua Liu et al.
Advanced Manufacturing and Logistics Optimization
article

Customized Flat Paper Pallet Picking Path Planning of Intelligent Forklift Based on GPOPS

Yongfei Xiao, Yang Zhang, Na Li, Zehua Liu, Zhengguang Ma, Chengrong Qin, Chun Hou, Hui Li
article en

Abstract

A flat paper pallet picking path planning approach is proposed in this paper to deal with the operation of forklift in confined working space. The constraints between the confined working space and the forklift position are constructed from the area relations. The path planning problem is divided into three stages and the linear velocity, angle of the forklift and position in the three different stages have corresponding constraints, respectively. Then, the pallet picking path planning problem is transformed into an optimal control problem. GPOPS is used to solve the nonlinear optimization problem and an effective forward and backward path planning method is proposed. The simulation illustrate the effectiveness of the proposed path planning method.

Guangxi University (CN), Qilu University of Technology (CN), Shandong Institute of Automation (CN), Luye Pharma (China) (CN), Shandong Academy of Sciences (CN)
Natural Science Foundation of Shandong Province
Openalex Percentile: Top 82%
Advanced Manufacturing and Logistics Optimization
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