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Vision-based excavator pose estimation for automatic control
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AI
DOI：10.1016/j.autcon.2023.105162.png)
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Abstract
En 中文
Hydraulic excavators, widely employed in harsh environments, have garnered increased attention in recent years from manufacturers and researchers for automatic operation, particularly through vision-based manipulator pose measurement. This paper utilized a mixed review method to explore the vision-based measurements as well as other applications. A quantitative analysis of computer vision (CV) applications on excavators was performed through a literature search, leading to the classification of these applications into three categories based on keywords. Subsequently, a comprehensive literature review identified four key requirements and challenges for vision-based measurement in the context of automatic control, followed by a discussion on the future prospects of marker-based and deep learning-based manipulator pose measurement for automatic control. This paper offers an in-depth examination of CV applications in excavators, emphasizing the pertinent challenges and forthcoming trends in vision-based manipulator pose measurement for automatic control.
Keywords:
Hydraulic excavator
Computer vision
Manipulator pose estimation
Automatic control
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