|
Abstract
|
Article Information:
Improved Fastslam2.0 Based on the H4 Filter for Intelligent Mobile Robot
Qi Zhang, Jiachen Ma and Qiang Liu
Corresponding Author: Qi Zhang
Submitted: March 26, 2012
Accepted: April 17, 2012
Published: August 15, 2012 |
Abstract:
|
This study proposes hybrid H∞ Fast SLAM algorithm as a robust and effective SLAM solution. In
usual FastSLAM2.0, a priori knowledge of the process and the statistics of measurement noise are assumed to
be Gaussian motion disturbances. However, in most application these matrixes are unknown or can’t be
assumed as Gaussian motion disturbances. The main advantage of the H∞ estimator is that it makes no
assumption about the disturbances and it has the ability which all conceivable disturbances can be satisfied. We
use the H∞ filter to handle the process and measurement noise covariance matrices Qt and Rt. And the k-step
look-ahead proposal distribution is added to calculate importance weight of particles. Simulation results in
different environments and consistency of the proposed approach are presented, demonstrating the superiority
of the proposed approach.
Key words: FastSLAM2.0, hybrid H∞ FastSLAM, intelligent mobile robot, simultaneous localization and mapping, the H∞ filter, ,
|
|
Abstract
|
PDF
|
HTML |
|
Cite this Reference:
Qi Zhang, Jiachen Ma and Qiang Liu, . Improved Fastslam2.0 Based on the H4 Filter for Intelligent Mobile Robot. Research Journal of Applied Sciences, Engineering and Technology, (16): 2748-2754.
|
|
|
|
 |
ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
 |
| Information |
|
|
|
|
| Sales & Services |
|
|
|
|
