Open AccessResearch on multi-load AGV path planning of weaving workshop based on time priority
Author(s) -
Li-zhen Du,
Shanfu Ke,
Zhen Wang,
Tao Jing,
Lianqing Yu,
Hongjun Liu
Publication year - 2019
Publication title -
mathematical biosciences and engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.451
H-Index - 45
eISSN - 1551-0018
pISSN - 1547-1063
DOI - 10.3934/mbe.2019113
Subject(s) - path (computing) , computer science , weaving , particle swarm optimization , convergence (economics) , mathematical optimization , motion planning , genetic algorithm , operations research , algorithm , engineering , artificial intelligence , mathematics , machine learning , robot , economics , economic growth , programming language , mechanical engineering
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.