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Mohamad Soffi Abd Razak
Universiti Teknologi MARA

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Simulation of simultaneous localization and mapping using 3D point cloud data Shuzlina Abdul-Rahman; Mohamad Soffi Abd Razak; Aliya Hasanah Binti Mohd Mushin; Raseeda Hamzah; Nordin Abu Bakar; Zalilah Abd Aziz
Indonesian Journal of Electrical Engineering and Computer Science Vol 16, No 2: November 2019
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v16.i2.pp941-949

Abstract

Abstract—This paper presents a simulation study of Simultaneous Localization and Mapping (SLAM) using 3D point cloud data from Light Detection and Ranging (LiDAR) technology.  Methods like simulation is useful to simplify the process of learning algorithms particularly when collecting and annotating large volumes of real data is impractical and expensive. In this study, a map of a given environment was constructed in Robotic Operating System platform with Gazebo Simulator. The paper begins by presenting the most currently popular algorithm that are widely used in SLAM namely Extended Kalman Filter, Graph SLAM and Fast SLAM. The study performed the simulations by using standard SLAM with Turtlebot and Husky robots. Husky robot was further compared with ACML algorithm. The results showed that Hector SLAM could reach the goal faster than ACML algorithm in a pre-defined map. Further studies in this field with other SLAM algorithms would certainly beneficial to many parties due to the demands of robotic application.
Co-Authors Aliya Hasanah Binti Mohd Mushin Nordin Abu Bakar Raseeda Hamzah Shuzlina Abdul-Rahman Zalilah Abd Aziz