Design Through Operation of an Image-Based Velocity Estimation System for Mars Landing

被引:0
|
作者
Andrew Johnson
Reg Willson
Yang Cheng
Jay Goguen
Chris Leger
Miguel Sanmartin
Larry Matthies
机构
[1] California Institute of Technology,Jet Propulsion Laboratory
关键词
velocity estimation; feature tracking; computer vision; robotics; Mars lander; Mars Exploration Rover; DIMES;
D O I
暂无
中图分类号
学科分类号
摘要
During the Mars Exploration Rover (MER) landings, the Descent Image Motion Estimation System (DIMES) was used for horizontal velocity estimation. The DIMES algorithm combined measurements from a descent camera, a radar altimeter, and an inertial measurement unit. To deal with large changes in scale and orientation between descent images, the algorithm used altitude and attitude measurements to rectify images to a level ground plane. Feature selection and tracking were employed in the rectified images to compute the horizontal motion between images. Differences of consecutive motion estimates were then compared to inertial measurements to verify correct feature tracking. DIMES combined sensor data from multiple sources in a novel way to create a low-cost, robust, and computationally efficient velocity estimation solution, and DIMES was the first robotics vision system used to control a spacecraft during planetary landing. This paper presents the design and implementation of the DIMES algorithm, the assessment of the algorithm performance using a high fidelity Monte Carlo simulation, validation of performance using field test data and the detailed results from the two landings on Mars.
引用
收藏
页码:319 / 341
页数:22
相关论文
共 50 条
  • [31] Single Image-Based Scene Visibility Estimation
    Li, Qin
    Li, Yi
    Xie, Bin
    IEEE ACCESS, 2019, 7 : 24430 - 24439
  • [32] Image-based vectorial velocity measurement of textured surfaces
    Horn, J
    TM-TECHNISCHES MESSEN, 2005, 72 (10) : 556 - 565
  • [33] Multiview Visibility Estimation for Image-Based Modeling
    张柳新
    裴明涛
    贾云得
    JournalofComputerScience&Technology, 2011, 26 (06) : 1000 - 1010
  • [34] An Evaluation of Image-Based Robot Orientation Estimation
    Cao, Juan
    Labrosse, Frederic
    Dee, Hannah
    TOWARDS AUTONOMOUS ROBOTIC SYSTEMS, 2014, 8069 : 135 - 147
  • [35] Image-based volume estimation for food in a bowl
    Jia, Wenyan
    Li, Boyang
    Xu, Qi
    Chen, Guangzong
    Mao, Zhi-Hong
    McCrory, Megan A.
    Baranowski, Tom
    Burke, Lora E.
    Lo, Benny
    Anderson, Alex K.
    Frost, Gary
    Sazonov, Edward
    Sun, Mingui
    JOURNAL OF FOOD ENGINEERING, 2024, 372
  • [36] Image-Based Pose Estimation of an Endoscopic Instrument
    Reilink, Rob
    Stramigioli, Stefano
    Misra, Sarthak
    2012 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2012, : 3555 - 3556
  • [37] Multiview Visibility Estimation for Image-Based Modeling
    Liu-Xin Zhang
    Ming-Tao Pei
    Yun-De Jia
    Journal of Computer Science and Technology, 2011, 26 : 1000 - 1010
  • [38] Image-based visual servoing with depth estimation
    Gongye, Qingxuan
    Cheng, Peng
    Dong, Jiuxiang
    TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL, 2022, 44 (09) : 1811 - 1823
  • [39] A Minimal Solution for Image-Based Sphere Estimation
    Toth, Tekla
    Hajder, Levente
    INTERNATIONAL JOURNAL OF COMPUTER VISION, 2023, 131 (06) : 1428 - 1447
  • [40] Image-based visual servoing with depth estimation
    Gongye, Qingxuan
    Cheng, Peng
    Dong, Jiuxiang
    Transactions of the Institute of Measurement and Control, 2022, 44 (09): : 1811 - 1823