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A dynamic SLAM algorithm based on improved YOLOv9S

delete2025-08-09
delete0
PRE
AI
Q
Qiguang Zhu
Y
Yuchao Zhao *
张
张浩峰 (Haofeng Zhang)
W
Weidong Chen
DOI：10.1016/j.asoc.2025.113700delete
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Abstract

Abstract

En 中文
• Enhanced YOLOv9-S with two novel modules for better detection in dynamic environments. • SLAM framework integrating improved YOLOv9-S with foreground separation. • The method’s accuracy was verified on TUM and dense point clouds were built in real scenarios.
Keywords:
YOLOv9-S
SLAM
foreground separation
dynamic environments
dense point clouds

Journal

Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
Papers:
1.4W
Citations:
4.8W

Organization

Y
Yanshan University
Scholars:
1.7W
Papers: 1.1W
Citations: 1.3W