Crane Pose Estimation Using UWB Real-Time Location System

被引:84
|
作者
Zhang, C. [1 ,2 ]
Hammad, A. [1 ]
Rodriguez, S. [1 ]
机构
[1] Concordia Univ, Concordia Inst Informat Syst Engn, Montreal, PQ H4B 1R6, Canada
[2] Xian Jiaotong Liverpool Univ, Dept Civil Engn, Suzhou 215123, Jiangsu, Peoples R China
关键词
Cranes; Pose estimation; Real-time location system; Ultra wideband;
D O I
10.1061/(ASCE)CP.1943-5487.0000172
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
Operating a crane is a complex job, which requires not only the experience of the operator, but also sufficient and appropriate real-time support to conceive and react to the environment. To help the crane operator, crane pose estimation is necessary to predict potential collisions. Environment perception technologies are essential to update environment information. Location data of the components of the cranes should be used to calculate the pose of the crane that can be used for collision avoidance. This paper aims to investigate how to collect and efficiently process the location data in near real time using ultra wideband (UWB) technology for providing intelligent support to crane operators. First, the requirements of using UWB technology in construction sites to track crane movements are defined. Then, the details of the UWB system setting method are investigated to decide the location of sensors and the number and location of tags attached to different components of a crane. A location data processing method is proposed to improve data quality by filtering noisy data and filling in missing data in near real time. An outdoor test is presented to demonstrate the feasibility of applying the proposed approach. Location data of a crane boom are collected and processed in near real time. The results of the test show a good potential to calculate the poses of crane booms using UWB real-time location system (RTLS). DOI: 10.1061/(ASCE)CP.1943-5487.0000172. (C) 2012 American Society of Civil Engineers.
引用
收藏
页码:625 / 637
页数:13
相关论文
共 50 条
  • [21] A Real-Time UWB Location and Tracking System Based on TWR-TDOA Estimation and a Simplified MPGA Layout Optimization
    Zhu, Yanping
    Huang, Lei
    Liu, Jing
    Cao, Zhongkang
    Chen, Jinli
    Mu, Zijian
    Mobile Information Systems, 2022, 2022
  • [22] Accurate, Robust, and Real-time Estimation of Finger Pose with a Motion Capture System
    Yun, Youngmok
    Agarwal, Priyanshu
    Deshpande, Ashish D.
    2013 IEEE/RSJ INTERNATIONAL CONFERENCE ON INTELLIGENT ROBOTS AND SYSTEMS (IROS), 2013, : 1626 - 1631
  • [23] Fast 3D Hand Pose Estimation for Real-time System
    Song, Jae-Hun
    Kang, Suk-Ju
    2020 17TH INTERNATIONAL SOC DESIGN CONFERENCE (ISOCC 2020), 2020, : 121 - 122
  • [24] Real-time camera pose estimation for sports fields
    Leonardo Citraro
    Pablo Márquez-Neila
    Stefano Savarè
    Vivek Jayaram
    Charles Dubout
    Félix Renaut
    Andrés Hasfura
    Horesh Ben Shitrit
    Pascal Fua
    Machine Vision and Applications, 2020, 31
  • [25] Accurate, robust, and real-time pose estimation of finger
    Department of Mechanical Engineering, University of Texas at Austin, Austin
    TX
    78712, United States
    J Dyn Syst Meas Control Trans ASME, 3
  • [26] Accurate, robust, and real-time pose estimation of finger
    Department of Mechanical Engineering, University of Texas at Austin, Austin
    TX
    78712, United States
    J Dyn Syst Meas Control Trans ASME, 3
  • [27] Accurate, robust, and real-time pose estimation of finger
    Department of Mechanical Engineering, University of Texas at Austin, Austin
    TX
    78712, United States
    J Dyn Syst Meas Control Trans ASME, 3
  • [28] Real-Time Articulated Hand Detection and Pose Estimation
    Panin, Giorgio
    Klose, Sebastian
    Knoll, Alois
    ADVANCES IN VISUAL COMPUTING, PT 2, PROCEEDINGS, 2009, 5876 : 1131 - 1140
  • [29] Accurate, Robust, and Real-Time Pose Estimation of Finger
    Yun, Youngmok
    Agarwal, Priyanshu
    Deshpande, Ashish D.
    JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME, 2015, 137 (03):
  • [30] Real-time camera pose estimation for sports fields
    Citraro, Leonardo
    Marquez-Neila, Pablo
    Savare, Stefano
    Jayaram, Vivek
    Dubout, Charles
    Renaut, Felix
    Hasfura, Andres
    Ben Shitrit, Horesh
    Fua, Pascal
    MACHINE VISION AND APPLICATIONS, 2020, 31 (03)