挖掘机
惯性测量装置
职位(财务)
计算机科学
身体姿势
估计
人工智能
计算机视觉
工程类
物理医学与康复
医学
业务
结构工程
系统工程
财务
作者
Jingyuan Tang,Han Luo,Peter T.-H. Wong,Jack C. Y. Cheng
出处
期刊:Lecture notes in civil engineering
日期:2020-07-14
卷期号:: 980-991
被引量:2
标识
DOI:10.1007/978-3-030-51295-8_68
摘要
Posture estimation provides basic mechanical information for remote control of construction equipment, safety analysis of construction sites and productivity analysis of construction projects. The rapid development of micro-machined electromechanical systems (MEMS) inertial sensors enables wide application of posture estimation in the construction industry. Previous studies have put efforts to orientation estimation, trajectory tracking, and activity recognition of construction equipment based on Inertia Measurement Units (IMU). As excavators are common and important heavy construction equipment on site, posture estimation of excavators is closely related to the safety of construction sites and automation of construction processes. Although there have been studies on IMU-based posture estimation of excavators, there is still a lack of studies that rigorously discuss the impact of IMU installation positions on posture estimation of construction equipment, especially excavators. Placing IMU sensors in appropriate positions on excavators would affect the accuracy of posture estimation. More practically, the installability issue also governs the installation positions. Hence, this paper investigates the influence of different IMU installation positions on posture estimation of excavators. Firstly, a systematic framework is proposed to estimate posture of excavators based on data collected by IMUs. Our experiments verify the feasibility of our proposed framework. Furthermore, the in-fluences of different installation positions of IMU are investigated, on the basis of accuracies represented by Euler angle. Considering accuracy and applicability, a scheme of installing IMU on excavators is discussed. This paper will provide a theoretical basis and a reliable operation scheme for IMU-based posture estimation of excavators in the future.
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