A Concise Guide to Feature Histograms with Applications to LIDAR-Based Spacecraft Relative Navigation

被引:14
|
作者
Rhodes, Andrew P. [1 ]
Christian, John A. [1 ]
Evans, Thomas [1 ]
机构
[1] West Virginia Univ, Dept Mech & Aerosp Engn, Morgantown, WV 26506 USA
来源
JOURNAL OF THE ASTRONAUTICAL SCIENCES | 2017年 / 64卷 / 04期
关键词
Relative navigation; Spacecraft; Feature histograms; OUR-CVFH; LIDAR;
D O I
10.1007/s40295-016-0108-y
中图分类号
V [航空、航天];
学科分类号
08 ; 0825 ;
摘要
With the availability and popularity of 3D sensors, it is advantageous to re-examine the use of point cloud descriptors for the purpose of pose estimation and spacecraft relative navigation. One popular descriptor is the oriented unique repeatable clustered viewpoint feature histogram (OUR-CVFH), which is most often utilized in personal and industrial robotics to simultaneously recognize and navigate relative to an object. Recent research into using the OUR-CVFH descriptor for spacecraft navigation has produced favorable results. Since OUR-CVFH is the most recent innovation in a large family of feature histogram point cloud descriptors, discussions of parameter settings and insights into its functionality are spread among various publications and online resources. This paper organizes the history of feature histogram point cloud descriptors for a straightforward explanation of their evolution. This article compiles all the requisite information needed to implement OUR-CVFH into one location, as well as providing useful suggestions on how to tune the generation parameters. This work is beneficial for anyone interested in using this histogram descriptor for object recognition or navigation - may it be personal robotics or spacecraft navigation.
引用
收藏
页码:414 / 445
页数:32
相关论文
共 50 条
  • [1] A Concise Guide to Feature Histograms with Applications to LIDAR-Based Spacecraft Relative Navigation
    Andrew P. Rhodes
    John A. Christian
    Thomas Evans
    The Journal of the Astronautical Sciences, 2017, 64 : 414 - 445
  • [2] Uncooperative Spacecraft Relative Navigation With LIDAR-Based Unscented Kalman Filter
    Opromolla, Roberto
    Nocerino, Alessia
    IEEE ACCESS, 2019, 7 : 180012 - 180026
  • [3] Analysis of LIDAR-based relative navigation performance during close-range rendezvous toward an uncooperative spacecraft
    Nocerino, Alessia
    Opromolla, Roberto
    Fasano, Giancarmine
    Grassi, Michele
    2020 IEEE 7TH INTERNATIONAL WORKSHOP ON METROLOGY FOR AEROSPACE (METROAEROSPACE), 2020, : 446 - 451
  • [4] LIDAR-based relative navigation with respect to non-cooperative objects
    Woods, John O.
    Christian, John A.
    ACTA ASTRONAUTICA, 2016, 126 : 298 - 311
  • [5] Design of lidar-based sensors and algorithms for determining the relative motion of an impaired spacecraft
    Fenton, RC
    Fullmer, RR
    Pack, RT
    SENSORS, AND COMMAND, CONTROL, COMMUNICATIONS, AND INTELLIGENCE (C31) TECHNOLOGIES FOR HOMELAND SECURITY AND HOMELAND DEFENSE IV, PTS 1 AND 2, 2005, 5778 : 809 - 818
  • [6] H∞ LIDAR odometry for spacecraft relative navigation
    Kechagias-Stamatis, Odysseas
    Aouf, Nabil
    IET RADAR SONAR AND NAVIGATION, 2019, 13 (05): : 771 - 775
  • [7] LiDAR-based Cooperative Relative Localization
    Dong, Jiqian
    Chen, Qi
    Qu, Deyuan
    Lu, Hongsheng
    Ganlath, Akila
    Yang, Qing
    Chen, Sikai
    Labi, Samuel
    2023 IEEE INTELLIGENT VEHICLES SYMPOSIUM, IV, 2023,
  • [8] LIDAR-based model reconstruction for spacecraft pose determination
    Perfetto, Davide Maria
    Opromolla, Roberto
    Grassi, Michele
    Schmitt, Christoph
    2019 IEEE 6TH INTERNATIONAL WORKSHOP ON METROLOGY FOR AEROSPACE (METROAEROSPACE), 2019, : 1 - 6
  • [9] Campus Guide: A Lidar-based Mobile Robot
    Liu, Minghao
    Hou, Zhixing
    Sun, Zezhou
    Yin, Ning
    Yang, Hang
    Wang, Ying
    Chu, Zhiqiang
    Kong, Hui
    2019 EUROPEAN CONFERENCE ON MOBILE ROBOTS (ECMR), 2019,
  • [10] FEATURE SELECTION FOR LIDAR-BASED GAIT RECOGNITION
    Galai, Bence
    Benedek, Csaba
    2015 INTERNATIONAL WORKSHOP ON COMPUTATIONAL INTELLIGENCE FOR MULTIMEDIA UNDERSTANDING (IWCIM), 2015,