Abstract
The ability to navigate mobile robots in the human environment is needed to keep a safe and reliable way to overcome the loss of the mobile robot position. To solve the localization problem for a mobile robot, particle filter algorithm was used to achieve the required robustness and accuracy. Particle filter is an algorithm based on estimation theory that used a set of particles to maintain hypothesis of the position of the mobile robot. In this paper, two objectives of the research project were described and presented. First, the simulation of particle filter localization algorithm in robot operating system (ROS). Second, the performance of the localization algorithm based on the accuracy of the robot’s state. In the simulation, the number of particles were used as parameter that will cause variation in the accuracy of the localization algorithm. It is concluded that the higher number of particles used will give a better accuracy of the robot’s state.
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Acknowledgements
The authors would like to thank the Centre for Research and Innovation Management (CRIM) of Universiti Teknikal Malaysia Melaka (UTeM) for the support under the grant number of RACER/2019/FKEKK-CETRI/F00404. A great appreciation goes to Centre for Telecommunication Research & Innovation (CeTRI), Fakulti Kejuruteraan Elektronik dan Kejuruteraan Komputer (FKEKK), Universiti Teknikal Malaysia Melaka (UTeM) and the Ministry of Higher Education of Malaysia for moral and operational support throughout the project.
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Sahabuddin, N.N.H.M., Yatim, N.M., Noh, Z.M., Wahab, N.A. (2022). Performance Analysis of Particle Filter Localization Algorithm for Mobile Robot. In: Isa, K., et al. Proceedings of the 12th National Technical Seminar on Unmanned System Technology 2020. Lecture Notes in Electrical Engineering, vol 770. Springer, Singapore. https://doi.org/10.1007/978-981-16-2406-3_7
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