Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot
This paper describes position control of autonomous mobile robot using combination of Kalman filter and Fuzzy logic techniques. Both techniques have been used to fuse information from internal and external sensors to navigate a typical mobile robot in an unknown environment. An obstacle avoidance al...
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Series: | International Journal of Advanced Robotic Systems |
Online Access: | https://doi.org/10.5772/5789 |
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doaj-8212022886c14fccb467fdf3edd22f852020-11-25T02:48:07ZengSAGE PublishingInternational Journal of Advanced Robotic Systems1729-88142005-09-01210.5772/578910.5772_5789Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile RobotRerngwut Choomuang0Nitin Afzulpurkar1 Asian Institute of Technology, School of Advanced Technologies, Pathumthani, Thailand Asian Institute of Technology, School of Advanced Technologies, Pathumthani, ThailandThis paper describes position control of autonomous mobile robot using combination of Kalman filter and Fuzzy logic techniques. Both techniques have been used to fuse information from internal and external sensors to navigate a typical mobile robot in an unknown environment. An obstacle avoidance algorithm utilizing stereo vision technique has been implemented for obstacle detection. The odometry errors due to systematic-errors (such as unequal wheel diameter, the effect of the encoder resolution etc.) and/or non-systematic errors (ground plane, wheel-slip etc.) contribute to various motion control problems of the robot. During the robot moves, whether straight-line and/or arc, create the position and orientation errors which depend on systematic and/or non-systematic odometry errors. The main concern in most of the navigating systems is to achieve the real-time and robustness performances to precisely control the robot movements. The objective of this research is to improve the position and the orientation of robot motion. From the simulation and experiments, we prove that the proposed mobile robot moves from start position to goal position with greater accuracy avoiding obstacles.https://doi.org/10.5772/5789 |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Rerngwut Choomuang Nitin Afzulpurkar |
spellingShingle |
Rerngwut Choomuang Nitin Afzulpurkar Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot International Journal of Advanced Robotic Systems |
author_facet |
Rerngwut Choomuang Nitin Afzulpurkar |
author_sort |
Rerngwut Choomuang |
title |
Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot |
title_short |
Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot |
title_full |
Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot |
title_fullStr |
Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot |
title_full_unstemmed |
Hybrid Kalman Filter/Fuzzy Logic based Position Control of Autonomous Mobile Robot |
title_sort |
hybrid kalman filter/fuzzy logic based position control of autonomous mobile robot |
publisher |
SAGE Publishing |
series |
International Journal of Advanced Robotic Systems |
issn |
1729-8814 |
publishDate |
2005-09-01 |
description |
This paper describes position control of autonomous mobile robot using combination of Kalman filter and Fuzzy logic techniques. Both techniques have been used to fuse information from internal and external sensors to navigate a typical mobile robot in an unknown environment. An obstacle avoidance algorithm utilizing stereo vision technique has been implemented for obstacle detection. The odometry errors due to systematic-errors (such as unequal wheel diameter, the effect of the encoder resolution etc.) and/or non-systematic errors (ground plane, wheel-slip etc.) contribute to various motion control problems of the robot. During the robot moves, whether straight-line and/or arc, create the position and orientation errors which depend on systematic and/or non-systematic odometry errors. The main concern in most of the navigating systems is to achieve the real-time and robustness performances to precisely control the robot movements. The objective of this research is to improve the position and the orientation of robot motion. From the simulation and experiments, we prove that the proposed mobile robot moves from start position to goal position with greater accuracy avoiding obstacles. |
url |
https://doi.org/10.5772/5789 |
work_keys_str_mv |
AT rerngwutchoomuang hybridkalmanfilterfuzzylogicbasedpositioncontrolofautonomousmobilerobot AT nitinafzulpurkar hybridkalmanfilterfuzzylogicbasedpositioncontrolofautonomousmobilerobot |
_version_ |
1724749910393225216 |