融合目标检测与DWA算法的AGV路径

doi:10.16180/j.cnki.issn1007-7820.2024.07.005

Abstract

Abstract:

In view of the path planning and navigation problem when the AGV forklift is in the situation of unknown environment information or dynamic change of environment, a method is proposed to obtain the target position by YOLOv5(You Only Look Once version 5) target detection algorithm. The global basic path is planned according to the target location, and the method of AGV path planning and navigation is integrated with DWA(Dynamic Window Approach) local dynamic path planning algorithm, so that the AGV forklift can quickly identify the target location and complete the path planning to reach the target location in the unknown environment or the environment with unknown local environment information. The experimental results show that compared with the previous method, the proposed method has good performance in terms of path length, time consumption and heading error of AGV forklift truck. The average path length is reduced by 12%, the average time consumption is reduced by about 5%, and the average error between the AGV heading and the target heading is within 5°. The proposed method can improve the working efficiency and flexibility of AGV forklift in unknown environment.

Key words: AGV, YOLOv5, DWA algorithm, global path planning, local path planning, target detection, navigation, automatic guidance

CLC Number:

TP242.6

LI Jun, LIU Hu, YANG Haima, WANG Yuan, XU Wencheng, HUANG Hongxin. Research on AGV Path Fusion of Object Detection and DWA Algorithm[J].Electronic Science and Technology, 2024, 37(7): 33-42.

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References 18

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网络模型	精度/%	FPS/frame·s^-1
改进YOLOv5s	90	30
原YOLOv5s	85	31
YOLOv5m	83	25
YOLOv5l	87	26
Faster RCNN	92	19
SSD	75	26

	路径长度/m	耗费时间/s	航向角度/(°)
基础DWA路径	15.268	27.2	-7
融合DWA路径	13.221	25.8	2
提升效果	减少13%	减少5%	-

	路径长度/m	耗费时间/s	航向角度/(°)
基础DWA路径	20.586	30.8	1
融合DWA路径	13.924	26.2	5
提升效果	减少32%	减少13%	-

	路径长度/m	耗费时间/s	航向角度/(°)
基础DWA路径	-	-	-
融合DWA路径	16.852	29.5	1
提升效果	-	-	-

	路径长度/m	耗费时间/s	航向角度/(°)
基础DWA路径	14.515	26.2	-50
融合DWA路径	13.235	25.6	0
提升效果	减少7%	减少2%	-

Research on AGV Path Fusion of Object Detection and DWA Algorithm

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	路径长度/m	耗费时间/s	航向角度/(°)
基础DWA路径	16.541	27.8	-40
融合DWA路径	14.332	26.5	4
提升效果	减少12%	减少4%	-

	路径长度/m	耗费时间/s	航向角/(°)
基础DWA路径	18.025	28.3	90
融合DWA路径	18.651	28.5	2
提升效果	增加3%	增加1%	-

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