A navigation method based on iterative extended Kalman filter fusing inertia and monocular vision

An extended Kalman and monocular vision technology, which is applied in the navigation field based on iterative extended Kalman filter fusion inertial and monocular vision, can solve the problems of small computational complexity, poor scalability, and increased computational load

Active Publication Date: 2019-02-22
SOUTHEAST UNIV
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Problems solved by technology

The tightly coupled method greatly increases the amount of calculation due to the addition of image feature information to the state vector, and its computational complexity has a linear relationship with the ra

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  • A navigation method based on iterative extended Kalman filter fusing inertia and monocular vision
  • A navigation method based on iterative extended Kalman filter fusing inertia and monocular vision
  • A navigation method based on iterative extended Kalman filter fusing inertia and monocular vision

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Embodiment Construction

[0117] Below in conjunction with accompanying drawing and specific embodiment the present invention is described in further detail:

[0118] The present invention provides a navigation method based on iterative extended Kalman filter fusion inertial and monocular vision. The present invention can maintain high precision in the process of long-term real-time positioning and navigation, and has the advantage of constant computational complexity between frames .

[0119] Such as Figure 1-4 As shown, a navigation method based on iterative extended Kalman filter fusion inertial and monocular vision, the method includes the following steps:

[0120] Step 1: Synchronize the time stamps of the information collected by the IMU and the monocular camera. The specific method is as follows:

[0121] The sampling frequency of an ordinary monocular camera is about 30HZ, while the sampling frequency of an IMU can reach hundreds or even thousands of hertz. On the robot operating system ROS...

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Abstract

The invention discloses a navigation method based on iterative extended Kalman filter fusing inertia and monocular vision. The method is as follows: A monocular camera and an inertial measurement unitare mounted on the carrier. A message filter in ROS is used to realize that time stamp synchronization of the monocular camera and the inertial measurement unit. The position, velocity and rotation obtained by IMU are taken as the state variables of the system, and the position and attitude information obtained by vision sensor is used as the observation variables to establish the system equation. The position, velocity and rotation obtained by IMU are used as state variables of the system. The information obtained from the two sensors is fused by an iterative extended Kalman filter to realize the real-time state estimation and navigation of the carrier. The invention can maintain high precision in the long-time real-time positioning and navigation process, and has the advantages that thecomputational complexity between frames does not change.

Description

technical field [0001] The invention relates to the technical field of navigation, in particular to a navigation method based on iterative extended Kalman filter fusion inertial and monocular vision. Background technique [0002] In recent years, navigation-related instruments and equipment have made breakthroughs, and the performance and accuracy of the equipment have been greatly improved. However, the navigation method implemented by a single sensor still has certain performance limitations. In order to meet the high-performance navigation requirements, integrated navigation methods have received extensive attention and development in recent years. The integrated navigation method combines a variety of navigation sensors, and uses the information measured by multiple sensors to compensate each other for their respective limitations to achieve high-precision navigation and enhance the robustness of the system. [0003] Inertial navigation is a comprehensive technology, wh...

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Application Information

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IPC IPC(8): G06K9/62G06K9/46G06T7/277G06T7/50G06T7/70
CPCG06T7/277G06T7/50G06T7/70G06V10/462G06F18/25
Inventor 徐晓苏袁杰杨阳梁紫依翁铖铖刘兴华
Owner SOUTHEAST UNIV
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