Visual-Inertial-Aided Navigation for High-Dynamic Motion in Built Environments Without Initial Conditions
Visual-Inertial-Aided Navigation for High-Dynamic Motion in Built Environments Without Initial Conditions
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DOI：
10.1109/tro.2011.2170332
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发表时间：
2012-02-01
影响因子：
7.8
通讯作者：
Sukkarieh, Salah
中科院分区：
文献类型：
--
作者：
Lupton, Todd;Sukkarieh, Salah
在本文中，我们提出了一种新的方法来融合观察从惯性测量单元（IMU）和视觉传感器，这样的惯性集成，包括重力估计的初始条件，可以快速恢复，并在一个线性的方式，从而消除任何需要特殊的初始化程序。该算法是使用一个图形化的同时定位和映射的方法，保证恒定的时间输出。本文讨论了技术方面的工作，包括可观测性和系统的能力，以估计规模在真实的时间。结果提出的系统，估计平台的位置，速度和姿态，以及重力矢量和传感器的对准和校准在线在一个建成的环境。本文讨论了系统设置，描述了实时集成的IMU数据与立体或单目视觉数据。我们专注于人体运动的目的，模仿高动态运动，以及提供一个定位系统，为未来的人机交互。
In this paper, we present a novel method to fuse observations from an inertial measurement unit (IMU) and visual sensors, such that initial conditions of the inertial integration, including gravity estimation, can be recovered quickly and in a linear manner, thus removing any need for special initialization procedures. The algorithm is implemented using a graphical simultaneous localization and mapping like approach that guarantees constant time output. This paper discusses the technical aspects of the work, including observability and the ability for the system to estimate scale in real time. Results are presented of the system, estimating the platforms position, velocity, and attitude, as well as gravity vector and sensor alignment and calibration on-line in a built environment. This paper discusses the system setup, describing the real-time integration of the IMU data with either stereo or monocular vision data. We focus on human motion for the purposes of emulating high-dynamic motion, as well as to provide a localization system for future human-robot interaction.