Research Status and Prospect of the Key Technologies for Environment Perception of Intelligent Excavators

With the urgent need of the industry and the continuous development of artificial intelligence, research into intelligent excavators has achieved certain progress. However, intelligent excavators often face strong vibrations, dense dust, and complex objectives. These have brought severe challenges to environmental perception, and are important research difficulties that must be overcome in realizing the practical engineering applications of intelligent excavators. Many researchers have studied these problems in reducing vibration and dust noise for light detection and ranging (LiDAR) scanners, multi-sensor information fusion, and the segmentation and recognition of 3D scenes. This paper reviews the research status of these key technologies and discusses their development trends.

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Publication Details

Journal
Applied Sciences
Published
2024-11-25
DOI
https://doi.org/10.3390/app142310919
Primary Topic
Industrial Vision Systems and Defect Detection
Type
article
Field-Weighted Citation Impact
0.00

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article

Research Status and Prospect of the Key Technologies for Environment Perception of Intelligent Excavators

Yi An, Yuchuan Du, Yunhao Cui, Jianhai Han
Applied Sciences
Industrial Vision Systems and Defect Detection
article

Research Status and Prospect of the Key Technologies for Environment Perception of Intelligent Excavators

Yi An, Yuchuan Du, Yunhao Cui, Jianhai Han
article en

Abstract

With the urgent need of the industry and the continuous development of artificial intelligence, research into intelligent excavators has achieved certain progress. However, intelligent excavators often face strong vibrations, dense dust, and complex objectives. These have brought severe challenges to environmental perception, and are important research difficulties that must be overcome in realizing the practical engineering applications of intelligent excavators. Many researchers have studied these problems in reducing vibration and dust noise for light detection and ranging (LiDAR) scanners, multi-sensor information fusion, and the segmentation and recognition of 3D scenes. This paper reviews the research status of these key technologies and discusses their development trends.

Applied SciencesVol. 14(23)
Henan University of Science and Technology (CN), Dalian University of Technology (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 70%
Industrial Vision Systems and Defect Detection
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