Visual-inertial structure from motion: observability and resolvability

被引:0
|
作者
Martinelli, Agostino [1 ]
机构
[1] INRIA Rhone Alpes, Montbonnot St Martin, France
关键词
PERCEPTION; VISION;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper provides two novel contributions. The former regards the observability of the visual-inertial structure from motion. It is proven that, the information contained in the data provided by a monocular camera which observes a single point-feature and by an Inertial Measurement Unit (IMU) allows estimating the absolute scale, the speed in the local frame, the absolute roll and pitch angles, the biases which affect the accelerometer's and the gyroscope's measurements, the magnitude of the gravitational acceleration and the extrinsic camera-IMU calibration. The latter contribution is the derivation of a new closed form solution to determine some of the previous observable quantities by only using few camera measurements collected during a short time interval and the data provided by the IMU during the same time interval. This closed-solution allows us to investigate the intrinsic properties of the visual-inertial structure from motion and in particular to identify the conditions under which the problem has a finite number of solutions. Specifically, it is shown that the problem can have a unique solution, two distinct solutions and infinite solutions depending on the trajectory, on the number of point-features and on their layout and on the number of camera images. The proposed closed solution is finally used in conjunction with a filter based approach in order to show its benefit.
引用
收藏
页码:4235 / 4242
页数:8
相关论文
共 50 条
  • [1] Visual-inertial structure from motion: observability vs minimum number of sensors
    Martinelli, Agostino
    2014 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2014, : 1020 - 1027
  • [2] Minimalistic sensor design in visual-inertial structure from motion
    Martinelli, Agostino
    2015 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2015, : 3313 - 3318
  • [3] Closed-Form Solution of Visual-Inertial Structure from Motion
    Martinelli, Agostino
    INTERNATIONAL JOURNAL OF COMPUTER VISION, 2014, 106 (02) : 138 - 152
  • [4] Closed-Form Solution of Visual-Inertial Structure from Motion
    Agostino Martinelli
    International Journal of Computer Vision, 2014, 106 : 138 - 152
  • [5] Control-enabled Observability in Visual-Inertial Odometry
    Bai, He
    Taylor, Clark N.
    2017 INTERNATIONAL CONFERENCE ON UNMANNED AIRCRAFT SYSTEMS (ICUAS'17), 2017, : 822 - 829
  • [6] Revisiting Visual-Inertial Structure-From-Motion for Odometry and SLAM Initialization
    Evangelidis, Georgios
    Micusik, Branislav
    IEEE ROBOTICS AND AUTOMATION LETTERS, 2021, 6 (02) : 1415 - 1422
  • [7] Control-enabled Observability and Sensitivity Functions in Visual-Inertial Odometry
    Bai, He
    Taylor, Clark N.
    JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS, 2019, 93 (1-2) : 289 - 301
  • [8] Control-enabled Observability and Sensitivity Functions in Visual-Inertial Odometry
    He Bai
    Clark N. Taylor
    Journal of Intelligent & Robotic Systems, 2019, 93 : 289 - 301
  • [9] Observability Analysis of IMU Intrinsic Parameters in Stereo Visual-Inertial Odometry
    Jung, Jae Hyung
    Heo, Sejong
    Park, Chan Gook
    IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT, 2020, 69 (10) : 7530 - 7541
  • [10] Visual-Inertial Fusion for Quadrotor Micro Air Vehicles with Improved Scale Observability
    Abeywardena, Dinuka
    Wang, Zhan
    Kodagoda, Sarath
    Dissanayake, Gamini
    2013 IEEE INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION (ICRA), 2013, : 3148 - 3153