Compensation for AUV’s Navigation Algorithm Based on Virtual Noise Model

Authors

Menglong Cao, College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266042, China;
Feifei Li, College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266042, China;
Xintao Liu, College of Automation and Electronic Engineering, Qingdao University of Science and Technology, Qingdao 266042, China;

Abstract

Abstract: The simultaneous localization and mapping (SLAM) of Autonomous underwater robot (AUV) is the key technology to realize the auto navigation for robot in the unknown environment of underwater, and it is one of the hot topics in the field of robotics research. In the framework of autonomous underwater robot SLAM, extended kalman filter (EKF) was applied to achieve the SLAM. For the model linearization errors and unknown noise statistics, EKF algorithm was used based on virtual noise compensation technology. This method could make the unknown model error into the virtual noise, and use the noise statistical to estimate the noise statistics. Constructing the AUV motion system model as a benchmark, the improved EKF algorithm was verified through matlab simulation from filtering accuracy, convergence and stability of the algorithm. The simulation results show that, compared with the traditional EKF algorithm, the improved EKF algorithm can get higher estimation precision, the expected effect is better, and can effectively improve the performance of nonlinear filtering.

Recommended Citation

Cao, Menglong; Li, Feifei; and Liu, Xintao (2020) "Compensation for AUV’s Navigation Algorithm Based on Virtual Noise Model," Journal of System Simulation: Vol. 28: Iss. 1, Article 33.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss1/33

First Page

242

Revised Date

2014-12-24

DOI Link

https://doi.org/

Last Page

248

CLC

TP242.6

Recommended Citation

Cao Menglong, Li Feifei, Liu Xintao. Compensation for AUV’s Navigation Algorithm Based on Virtual Noise Model[J]. Journal of System Simulation, 2016, 28(1): 242-248.