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All Journal Bulletin of Electrical Engineering and Informatics Indonesian Journal of Electrical Engineering and Computer Science
Zalilah Abd Aziz
Universiti Teknologi MARA
Electrical & Electronics Engineering

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Visual analytics of 3D LiDAR point clouds in robotics operating systems Alia Mohd Azri; Shuzlina Abdul-Rahman; Raseeda Hamzah; Zalilah Abd Aziz; Nordin Abu Bakar
Bulletin of Electrical Engineering and Informatics Vol 9, No 2: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (329.326 KB) | DOI: 10.11591/eei.v9i2.2061

Abstract

This paper presents visual analytics of 3D LiDAR point clouds in robotics operating system. In this study, experiment on simultaneous localization and mapping (SLAM) using point cloud data derived from the light detection and ranging (LiDAR) technology is conducted. We argue that one of the weaknesses of the SLAM algorithm is in the localization process of the landmarks. Existing algorithms such as grid mapping and monte carlo have limitations in dealing with 3D environment data that have led to less accurate estimation. Therefore, this research proposes the SLAM algorithm based on real-time appearance-based (RTAB) and makes use of the red green blue (RGB) camera for visualisation. The algorithm was tested by using the map data that was collected and simulated on the robot operating system (ROS) in Linux environment. We present the results and demonstrates that the map produced by RTAB is better compared to its counterparts. In addition, the probability for the estimated location is improved which allows for better vehicle maneuverability.
A review on various methods of collaborative computing Mohd Afiq Bin Zamanhuri; Zalilah Abd Aziz; Rose Hafsah Abd Rauf; Elly Johana Johan; Noratikah Shamsudin
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.pp1002-1008

Abstract

Currently, mosques in Malaysia distribute their lecture schedules either on paper-based form or by uploading the schedule on their social media platform. This has some disadvantages such as paper schedules are susceptible to damages and information on social media platform is often not updated to current changes. Collaborative Computing is a system that enable individuals to work together remotely by making use of the reach ability of the internet. In order to utilise the Internet’s obvious advantages over paper-based and rapid information distribution and asynchronous communication, a review is conducted to study the available methods of collaborative computing, further analyse current research papers. Result shows that Centralized Computing method is the most suitable method for developing collaborative mobile application for Islamic Lectures schedule.
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 Alia Mohd Azri Aliya Hasanah Binti Mohd Mushin Elly Johana Johan Mohamad Soffi Abd Razak Mohd Afiq Bin Zamanhuri Noratikah Shamsudin Nordin Abu Bakar Raseeda Hamzah Rose Hafsah Abd Rauf Shuzlina Abdul-Rahman