Authors
Barry Loh Tze Yuen, Khairul Salleh Mohamed Sahari, Zubaidi Faiesal Mohamad Rafaai
Corresponding Author
Barry Loh Tze Yuen
Available Online 1 September 2017.
DOI
https://doi.org/10.2991/jrnal.2017.4.2.3How to use a DOI?
Keywords
SLAM, ROS, Gaussian Noise, map generation, exploration.
Abstract
Rao-Blackwellized Particle Filter (RBPF) is used in this paper to solve the Simultaneous Localization and Mapping (SLAM) problem. RBPF algorithm uses particle filter where each particle carries an individual map of the environment. With the usage of Robot Operating System (ROS), GMapping package was used as a basis for map generation and SLAM. To improve the map generation, Gaussian noise was introduced to the data from laser range finder and also the odometry from the robot Pioneer P3AT’s pose. The introduced algorithm was successful in decreasing the uncertainty as well as increased the knowledge of each particle in the estimation of the robot’s pose, proven through practical experiment. Exploration experiments were also carried out to test the performance of P3AT based on our proposed method.

Copyright
© 2013, the Authors. Published by ALife Robotics Corp. Ltd.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).