Mohd Marzuki Mustafa
Universiti Kebangsaan Malaysia

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GA-based Optimisation of a LiDAR Feedback Autonomous Mobile Robot Navigation System Siti Nurhafizah Anual; Mohd Faisal Ibrahim; Nurhana Ibrahim; Aini Hussain; Mohd Marzuki Mustafa; Aqilah Baseri Huddin; Fazida Hanim Hashim
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (385.649 KB) | DOI: 10.11591/eei.v7i3.1275

Abstract

Autonomous mobile robots require an efficient navigation system in order to navigate from one location to another location fast and safe without hitting static or dynamic obstacles. A light-detection-and-ranging (LiDAR) based autonomous robot navigation is a multi-component navigation system consists of various parameters to be configured. With such structure and sometimes involving conflicting parameters, the process of determining the best configuration for the system is a non-trivial task. This work presents an optimisation method using Genetic algorithm (GA) to configure such navigation system with tuned parameters automatically. The proposed method can optimise parameters of a few components in a navigation system concurrently. The representation of chromosome and fitness function of GA for this specific robotic problem are discussed. The experimental results from simulation and real hardware show that the optimised navigation system outperforms a manually-tuned navigation system of an indoor mobile robot in terms of navigation time.
Newly Developed Nonlinear Vehicle Model for an Active Anti-roll Bar System Noraishikin Binti Zulkarnain; Hairi Zamzuri; Sarah ’Atifah Saruchi; Mohd Marzuki Mustafa; Siti Salasiah Mokri; Nurbaiti Wahid; Siti Nor Zawani Ahmmad; Alias Jedi
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (349.242 KB) | DOI: 10.11591/eei.v7i4.1185

Abstract

This paper presents the development of a newly developed nonlinear vehicle model is used in the validation process of the vehicle model. The parameters chosen in a newly developed vehicle model is developed based on CARSIM vehicle model by using non-dominated sorting genetic algorithm version II (NSGA-II) optimization method. The ride comfort and handling performances have been one of the main objective to fulfil the expectation of customers in the vehicle development. Full nonlinear vehicle model which consists of ride, handling and Magic tyre subsystems has been derived and developed in MATLAB/Simulink. Then, optimum values of the full nonlinear vehicle parameters are investigated by using NSGA-II. The two objective functions are established based on RMS error between simulation and benchmark system. A stiffer suspension provides good stability and handling during manoeuvres while softer suspension gives better ride quality. The final results indicated that the newly developed nonlinear vehicle model is behaving accurately with input ride and manoeuvre. The outputs trend are successfully replicated.
Newly Developed Nonlinear Vehicle Model for an Active Anti-roll Bar System Noraishikin Binti Zulkarnain; Hairi Zamzuri; Sarah ’Atifah Saruchi; Mohd Marzuki Mustafa; Siti Salasiah Mokri; Nurbaiti Wahid; Siti Nor Zawani Ahmmad; Alias Jedi
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (349.242 KB) | DOI: 10.11591/eei.v7i4.1185

Abstract

This paper presents the development of a newly developed nonlinear vehicle model is used in the validation process of the vehicle model. The parameters chosen in a newly developed vehicle model is developed based on CARSIM vehicle model by using non-dominated sorting genetic algorithm version II (NSGA-II) optimization method. The ride comfort and handling performances have been one of the main objective to fulfil the expectation of customers in the vehicle development. Full nonlinear vehicle model which consists of ride, handling and Magic tyre subsystems has been derived and developed in MATLAB/Simulink. Then, optimum values of the full nonlinear vehicle parameters are investigated by using NSGA-II. The two objective functions are established based on RMS error between simulation and benchmark system. A stiffer suspension provides good stability and handling during manoeuvres while softer suspension gives better ride quality. The final results indicated that the newly developed nonlinear vehicle model is behaving accurately with input ride and manoeuvre. The outputs trend are successfully replicated.
GA-based Optimisation of a LiDAR Feedback Autonomous Mobile Robot Navigation System Siti Nurhafizah Anual; Mohd Faisal Ibrahim; Nurhana Ibrahim; Aini Hussain; Mohd Marzuki Mustafa; Aqilah Baseri Huddin; Fazida Hanim Hashim
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (385.649 KB) | DOI: 10.11591/eei.v7i3.1275

Abstract

Autonomous mobile robots require an efficient navigation system in order to navigate from one location to another location fast and safe without hitting static or dynamic obstacles. A light-detection-and-ranging (LiDAR) based autonomous robot navigation is a multi-component navigation system consists of various parameters to be configured. With such structure and sometimes involving conflicting parameters, the process of determining the best configuration for the system is a non-trivial task. This work presents an optimisation method using Genetic algorithm (GA) to configure such navigation system with tuned parameters automatically. The proposed method can optimise parameters of a few components in a navigation system concurrently. The representation of chromosome and fitness function of GA for this specific robotic problem are discussed. The experimental results from simulation and real hardware show that the optimised navigation system outperforms a manually-tuned navigation system of an indoor mobile robot in terms of navigation time.
Newly Developed Nonlinear Vehicle Model for an Active Anti-roll Bar System Noraishikin Binti Zulkarnain; Hairi Zamzuri; Sarah ’Atifah Saruchi; Mohd Marzuki Mustafa; Siti Salasiah Mokri; Nurbaiti Wahid; Siti Nor Zawani Ahmmad; Alias Jedi
Bulletin of Electrical Engineering and Informatics Vol 7, No 4: December 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (349.242 KB) | DOI: 10.11591/eei.v7i4.1185

Abstract

This paper presents the development of a newly developed nonlinear vehicle model is used in the validation process of the vehicle model. The parameters chosen in a newly developed vehicle model is developed based on CARSIM vehicle model by using non-dominated sorting genetic algorithm version II (NSGA-II) optimization method. The ride comfort and handling performances have been one of the main objective to fulfil the expectation of customers in the vehicle development. Full nonlinear vehicle model which consists of ride, handling and Magic tyre subsystems has been derived and developed in MATLAB/Simulink. Then, optimum values of the full nonlinear vehicle parameters are investigated by using NSGA-II. The two objective functions are established based on RMS error between simulation and benchmark system. A stiffer suspension provides good stability and handling during manoeuvres while softer suspension gives better ride quality. The final results indicated that the newly developed nonlinear vehicle model is behaving accurately with input ride and manoeuvre. The outputs trend are successfully replicated.
GA-based Optimisation of a LiDAR Feedback Autonomous Mobile Robot Navigation System Siti Nurhafizah Anual; Mohd Faisal Ibrahim; Nurhana Ibrahim; Aini Hussain; Mohd Marzuki Mustafa; Aqilah Baseri Huddin; Fazida Hanim Hashim
Bulletin of Electrical Engineering and Informatics Vol 7, No 3: September 2018
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (385.649 KB) | DOI: 10.11591/eei.v7i3.1275

Abstract

Autonomous mobile robots require an efficient navigation system in order to navigate from one location to another location fast and safe without hitting static or dynamic obstacles. A light-detection-and-ranging (LiDAR) based autonomous robot navigation is a multi-component navigation system consists of various parameters to be configured. With such structure and sometimes involving conflicting parameters, the process of determining the best configuration for the system is a non-trivial task. This work presents an optimisation method using Genetic algorithm (GA) to configure such navigation system with tuned parameters automatically. The proposed method can optimise parameters of a few components in a navigation system concurrently. The representation of chromosome and fitness function of GA for this specific robotic problem are discussed. The experimental results from simulation and real hardware show that the optimised navigation system outperforms a manually-tuned navigation system of an indoor mobile robot in terms of navigation time.
Retina blood vessel extraction based on kirsch’s template method Nur Syazlin Zolkifli; Ain Nazari; Mohd Marzuki Mustafa; Wan NurShazwani Wan Zakaria; Nor Surayahani Suriani; Wan Nur Hafsha Wan Kairuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp318-325

Abstract

Analysis on the retina blood vessels from fundus images have been widely used in the medical community to detect the disorder condition in the blood vessels. An automated tracing of retina blood vessel can help to provide valuable computer-assisted diagnosis for the ophthalmic disorders. Thus, it helps to reduce the time for the ophthalmologist to analyses and diagnose the result of the fundus image of patient. The purpose of this research is to build an algorithm to trace the retina blood vessels. The method to be used in this research consist of two parts which are the pre-processing part and the feature extraction by using the Kirsch’s template. Combining the pre-processing at the early stage and feature extraction at the next stage is applied to extract the edges of the blood vessels.  The proposed algorithm was verified by using two online databases, DRIVE and HRF to validate the performance measures. Hence, proposed method is capable to extract the retina blood vessel and give the accuracy of 0.7917, the sensitivity of 0.9077 and the specificity of 0.7215. In conclusion, the extraction of the blood vessels is highly recommended as the early screening stage for the eye diseases beneficially.
Glaucoma detection of retinal images based on boundary segmentation Noraina Alia Zainudin; Ain Nazari; Mohd Marzuki Mustafa; Wan NurShazwani Wan Zakaria; Nor Surayahani Suriani; Wan Nur Hafsha Wan Kairuddin
Indonesian Journal of Electrical Engineering and Computer Science Vol 18, No 1: April 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v18.i1.pp377-384

Abstract

The rapid growth of technology makes it possible to implement in immediate diagnosis for patients using image processing. By using morphological processing and adaptive thresholding method for segmentation of optic disc and optic cup, various sizes of retinal fundus images captured through fundus camera from online databases can be processed. This paper explains the use of color channel separation method for pre-processing to remove noise for better optic disc and optic cup segmentation. Noise removal will improve image quality and in return help to increase segmentation standard. Then, morphological processing and adaptive thresholding method is used to extract out optic disc and optic cup from fundus image. The proposed method is tested on two publicly available online databases: RIM-ONE and DRIONS-DB. On RIM-ONE database, the average PSNR value acquired is 0.01891 and MSE is 65.62625. Meanwhile, for DRIONS-DB database, the best PSNR is 64.0928 and the MSE is 0.02647. In conclusion, the proposed method can successfully filter out any unwanted noise in the image and are able to help clearer optic disc and optic cup segmentation to be performed.