{"id":6633,"date":"2026-08-16T21:50:18","date_gmt":"2026-08-16T13:50:18","guid":{"rendered":"\/jase\/?post_type=tkuisotope&p=6633"},"modified":"2026-08-23T15:32:09","modified_gmt":"2026-08-23T07:32:09","slug":"auto-maps-generation-through-self-path-generation-in-ros-based-robot-navigation","status":"publish","type":"tkuisotope","link":"\/jase\/?tkuisotope=auto-maps-generation-through-self-path-generation-in-ros-based-robot-navigation","title":{"rendered":"Auto-maps-generation through Self-path-generation in ROS-based Robot Navigation"},"content":{"rendered":"\n
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<\/i> 2018<\/a><\/p>\n<\/div>\n\n\n\n

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<\/i> Volume 21, Issue 3<\/a><\/p>\n<\/div>\n\n\n\n

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Shih-An Li1<\/sup>, Hsuan-Ming Feng2*<\/sup><\/i><\/a>, Kung-Han Chen1<\/sup>, Jian-Ming Lin1<\/sup>, and Li-Hsiang Chou1<\/sup><\/p>\n\n\n\n

1<\/sup>Department of Electrical Engineering, Tamkang University, Tamsui, Taiwan 251, R.O.C.<\/p>\n\n\n\n

2<\/sup>Department of Computer Science and Information Engineering, National Quemoy University, Kinmen, Taiwan 892, R.O.C.<\/p>\n<\/div>\n\n\n\n

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Received:\u00a0October 25, 2017
Accepted:\u00a0February 27, 2018
Publication Date:\u00a0August 16 2026<\/p>\n<\/div>\n<\/div>\n\n\n\n

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Gazebo platform in the ROS architecture.<\/p>\n<\/div>\n<\/div>\n\n\n\n

<\/i> Copyright <\/strong>The Author(s). This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0)<\/a>, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are cited.<\/p>\n\n\n\n

Download Citation:  BibTeX <\/a>| http:\/\/dx.doi.org\/10.6180\/jase.201809_21(3).0006<\/a>  <\/p>\n\n\n\n

Download PDF<\/a><\/p>\n\n\n\n

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This paper applies a virtual robot operating system (ROS) platform to concurrently perform the automatic map generation and appropriate path planning for robot navigation applications. The powerful ROS works as a self-constructed robotic facility to perfectly achieve the maps generation and robot localization functions. LiDAR dynamically scanned the required information from the outsides environment and matched the visual maps for reaching the best path coverage and predicting the accurate robot location. ROS-based GAZEBO plant with the flexible and friendly interface is taken to simultaneously imitate the robot environment. In the illustrated experiments, an efficient A* algorithm is approved to build the near optimal routing path within one second executing time. Hector SLAM technology is employed to automatically generate the robot maps for completing nonlinear and complexed navigation applications.<\/p>\n\n\n\n

Keywords: Robot Operating System; GAZEBO Simulator; A* Algorithm; LiDAR<\/em><\/p>\n\n\n\n

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