Path planning for AGVs in 4D millimeter-wave radar antenna module production plant

Aiming at the strict requirements of 4D millimeter-wave radar antenna module production, path planning is carried out for the automatic guided vehicle (AGV) of the automated transportation system in the production workshop. Firstly, the search neighborhood of the traditional A* algorithm is improved, and the four-neighborhood search method is used to improve the directivity between the starting point and the end point, which effectively solves the problem of long search time; then the search path is locally optimized by using Bessel curves for smoothing, which effectively solves the problem of many inflection points, and improves the smoothing degree of the path. Finally, the simulation verification of two sets of data, the first set of data using the fusion of the improved A* algorithm compared to the traditional A* algorithm in the search time reduced by 29.30%, the path length reduced by 2.39%; the second set of data using the fusion of the improved A* algorithm compared to the traditional A* algorithm in the search time reduced by 22.91%, the path length reduced by 1.82%, which can be used for the automated production workshop Provide an effective theoretical basis.

Authors

Institutions

Publication Details

Published
2025-05-27
DOI
https://doi.org/10.1117/12.3065563
Primary Topic
Advanced Manufacturing and Logistics Optimization
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Path planning for AGVs in 4D millimeter-wave radar antenna module production plant

Jun Xu, Lihua Zhang
Advanced Manufacturing and Logistics Optimization
article

Path planning for AGVs in 4D millimeter-wave radar antenna module production plant

Jun Xu, Lihua Zhang
article en

Abstract

Aiming at the strict requirements of 4D millimeter-wave radar antenna module production, path planning is carried out for the automatic guided vehicle (AGV) of the automated transportation system in the production workshop. Firstly, the search neighborhood of the traditional A* algorithm is improved, and the four-neighborhood search method is used to improve the directivity between the starting point and the end point, which effectively solves the problem of long search time; then the search path is locally optimized by using Bessel curves for smoothing, which effectively solves the problem of many inflection points, and improves the smoothing degree of the path. Finally, the simulation verification of two sets of data, the first set of data using the fusion of the improved A* algorithm compared to the traditional A* algorithm in the search time reduced by 29.30%, the path length reduced by 2.39%; the second set of data using the fusion of the improved A* algorithm compared to the traditional A* algorithm in the search time reduced by 22.91%, the path length reduced by 1.82%, which can be used for the automated production workshop Provide an effective theoretical basis.

Jiangsu University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 84%
Advanced Manufacturing and Logistics Optimization
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.