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面向AGV环境感知的图像点云融合研究综述

王荣儿 伍济钢

计算机科学与探索2026,Vol.20Issue(4):965-976,12.
计算机科学与探索2026,Vol.20Issue(4):965-976,12.DOI:10.3778/j.issn.1673-9418.2504068

面向AGV环境感知的图像点云融合研究综述

Review of Image-Point Cloud Fusion Research for AGV Environment Perception

王荣儿 1伍济钢1

作者信息

  • 1. 湖南科技大学机电工程学院,湖南湘潭 411100||湖南科技大学机械设备健康维护湖南省重点实验室,湖南湘潭 411100
  • 折叠

摘要

Abstract

With the rapid development of automated industrial production lines and intelligent logistics and warehousing systems,automated guided vehicle(AGV)serves as core component in industrial automation and smart manufacturing.The environmental perception capability constitutes a prerequisite for achieving high-precision autonomous navigation and intelligent operations.The deep integration of artificial intelligence and multimodal sensing technologies enables AGV to overcome the limitations of traditional perception modes,realizing dynamic understanding and autonomous re-sponses in complex industrial scenarios.Image-point cloud fusion perception technology has emerged as a critical break-through direction for enhancing AGV perception robustness and adaptability,leveraging its advantages in 3D spatial reso-lution and semantic information complementarity.The evolutionary trajectory of image-point cloud fusion technology in AGV environmental perception is systematically reviewed,while performance boundaries and application scenarios of typical fusion strategies are compared,along with deep learning-based fusion methodologies being analyzed.In response to bottleneck challenges including multi-sensor calibration and long-term stability,algorithm real-time performance,con-flicts between edge computing resources and algorithm complexity,and extreme condition adaptability,this paper explores technical development directions from four dimensions:unsupervised online calibration,dynamic perception-decision closed-loop optimization,algorithm-task co-design,and adaptive perception in extreme scenarios.Theoretical foundations and technical references are provided for the construction of safer,more efficient,and universally applicable AGV environmental perception systems through these proposed approaches.

关键词

自动导引车(AGV)/图像点云融合/深度学习/环境感知/工业场景

Key words

automated guided vehicle(AGV)/image-point cloud fusion/deep learning/environmental perception/indus-trial scenarios

分类

信息技术与安全科学

引用本文复制引用

王荣儿,伍济钢..面向AGV环境感知的图像点云融合研究综述[J].计算机科学与探索,2026,20(4):965-976,12.

基金项目

湖南省科技创新计划项目重点项目(HST2313) (HST2313)

湖南省自然科学省市联合基金项目(2022JJ50129).This work was supported by the Key Project of Hunan Science and Technology Innovation Plan(HST2313),and the Hunan Provincial Natural Science Joint Fund Project(2022JJ50129). (2022JJ50129)

计算机科学与探索

1673-9418

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