A Robust SINS/VO Integrated Navigation Algorithm Based on RHCKF for Unmanned Ground Vehicles | Zendy

Ya Zhang | Zendy; Fei Yu | Zendy; Yanyan Wang | Zendy; Kai Wang | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Open Access

A Robust SINS/VO Integrated Navigation Algorithm Based on RHCKF for Unmanned Ground Vehicles

Author(s) -

Ya Zhang,

Fei Yu,

Yanyan Wang,

Kai Wang

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2873292

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

High precision localization information is the precondition of unmanned ground vehicles. But the global navigation satellite system (GNSS) signal turns unreliable in urban and forest areas since it is blocked by buildings and trees easily, which causes decline of localization accuracy. In order to solve this problem, an integrated navigation system based on the strapdown inertial navigation system and binocular camera visual odometer is utilized in this paper to provide navigation parameters for unmanned ground vehicles when the GNSS signal denies. However, the existing integrated navigation algorithm cannot meet the requirement of the high precision localization for unmanned ground vehicles because of the uncertainty and nonlinearity. As a result, a robust nonlinear filter based on the

$H_\infty $

filter and the cubature Kalman filter, named RHCKF, is proposed in this paper, adopted in unmanned vehicle navigation. Simulation and real test are both carried out to verify the effectiveness of the novel navigation algorithm when the GNSS signal denies.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.

Having issues? You can contact us here

Accelerating Research