| Literature DB >> 31137212 |
Li Zhen Du1, Shan Fu Ke1, Zhen Wang1, Jing Tao2, Lian Qing Yu1, Hong Jun Li1.
Abstract
The multi-load AGV (Automatic Guided Vehicle) is a new kind of materials handling equipment used to load cloth automatically in an intelligent weaving workshop. It can transport multiple rolls of cloth and choose the correct, most effective path to improve the transportation efficiency without people engaged in. This paper creates a feasible path topology according to the layout of the workshop and the logistics environment, and uses the Warshall-Floyd algorithm to search for the optimal route between two arbitrary points. The aim of the path planning is to maximize the machine efficiency, which is constrained by environmental limits, load limits and work limits. This paper establishes the mathematical model of the path planning problem using the mixed genetic particle swarm optimization algorithm (GA-PSO) to solve the problem, and the particle iteration mechanism based on the time priority is proposed to make the evolution more directional and accelerate the convergence speed of the algorithm. The effectiveness and practicability of the model and methods are verified by simulation and benefit analysis.Entities:
Keywords: GA-PSO algorithm ; intelligent weaving workshop ; multi-load AGV ; path planning ; time priority
Mesh:
Year: 2019 PMID: 31137212 DOI: 10.3934/mbe.2019113
Source DB: PubMed Journal: Math Biosci Eng ISSN: 1547-1063 Impact factor: 2.080