Azali Saudi

Fast lane detection with Randomized Hough Transform

Lane detection is an essential component of autonomous mobile robot applications. Any lane detection method has to deal with the varying conditions of the lane and surrounding that the robot would encounter while moving. Lane detection procedure can provide estimates for the position and orientation of the robot within the lane and also can provide a reference system for locating other obstacles in the path of the robot. In this paper we present a method for lane detection in video frames of a camera mounted on top of the mobile robot. Given video input from the camera, the gradient of the current lane in the near field of view are automatically detected. Randomized Hough Transform is used for extracting parametric curves from the images acquired. A priori knowledge of the lane position is assumed for better accuracy of lane detection.

Mel-frequency cepstral coefficient analysis in speech recognition

Speech recognition is a major topic in speech signal processing. Speech recognition is considered as one of the most popular and reliable biometric technologies used in automatic personal identification systems. Speech recognition systems are used for variety of applications such as multimedia browsing tool, access centre, security and finance. It allows people work in active environment to use computer. For a reliable and high accuracy of speech recognition, simple and efficient representation methods are required. In this paper, the zero crossing extraction and the energy level detection are applied to the recorded speech signal for voiced/unvoiced area detection. The detected voiced signals are applied for segmentation. Further, the MFCC method is applied to all of the segmented windows. The extracted MFCC data are further used as inputs for neural network training.

Multi-objective artificial evolution of RF-localization behavior and neural structures in mobile robots

This paper investigates the utilization of a multi- objective approach for evolving artificial neural networks (ANNs) that act as a controller for radio frequency (RF)- localization behavior of a virtual Khepera robot simulated in a 3D, physics-based environment. The non-elitist and elitist Pareto-frontier Differential Evolution (PDE) algorithm are used to generate the Pareto optimal sets of ANNs that optimize the conflicting objectives of maximizing the virtual Khepera robots behavior for homing towards a RF signal source and minimizing the number of hidden neurons used in its feedforward ANNs controller. A new fitness function which involved maximizing average wheels speed and detection of the RF signal source is also proposed. The experimentation results showed that the virtual Khepera robot was able to move towards to the target with using only a small number of hidden neurons. Furthermore, the testing results also showed that the success rate for the robot to achieve the signal source was higher when the elitist PDE-EMO algorithm was used. The path analysis of the Pareto controllers elucidated many different behaviors in terms of providing a successful homing behavior for the robot to attain the RF signal source.

Numerical technique for robot path planning using four Point-EG iterative method

Path planning is an important issue as it allows a robot to get from start point to goal point. In this work, we attempt to solve robot path planning problem iteratively using numerical technique. It is based on the use of Laplaces Equation to compute potential function in the configuration space of a mobile robot. This paper proposed a block iterative method known as 4 Point-EG for solving robot path planning problem. By employing a finite-difference technique, the experiment shows that it able to generate smooth path between the start and goal points. Furthermore, the simulation results show that 4 Point-EG performs faster than the previous method in generating path for mobile robot motion.

Path Planning for Indoor Mobile Robot using Half-Sweep SOR via Nine-Point Laplacian (HSSOR9L)

This paper proposed fast Half-Sweep SOR via Nine-Point Laplacian (HSSOR9L) iterative method for solving path planning problem for a mobile robot operating in indoor environment model. It is based on the use of Laplaces Equation to constraint the distribution of potential values in the environment of the robot. Fast computation with half-sweep iteration is obtained by considering only half of whole points in the configuration model. The inclusion of SOR and 9-point Laplacian into the formulation further speeds up the computation. The simulation results show that HSSOR9L performs much faster than the previous iterative methods in computing the potntial values to be used for generating smooth path from a given initial point to a specified goal position. Keywords - Robot path planning, Half-Sweep SOR via Nine-Point Laplacian (HSSOR9L), Laplaces Equation, Harmonic functions The capability of moving quickly from a given initial point to a specified goal point is essential for truly autonomous mobile robot operating in indoor environment. While exploring the environment, the robot must avoid any obstacles and walls that obstructing its motion. Therefore, path planning problem pose as an important issue in building a robust indoor mobile robot. This study proposed a global numerical approach in solving this difficult path planning problem. It is based on the theory of a steady-state heat transfer, in which the configuration space is modeled with Laplaces equation. Consequently, the solutions of Laplaces equation also called harmonic functions that represent temperature values distribution in the configuration space will be used to simulate the generation of path for mobile robot motion. In the past, various approaches had been used to obtain harmonic functions, but the most common method is via numerical techniques due to the availability of fast processing machine and their elegant and efficiency in solving the problem. In this study, we investigate the performance of Half-Sweep SOR via Nine-Point Laplacian (HSSOR9L) in computing the harmonic functions to generate path for a mobile robot operating in varying sizes of indoor environment model. II.

Implicit finite difference solution for time-fractional diffusion equations using AOR method

In this paper, we derive an implicit finite difference approximation equation of the one-dimensional linear time fractional diffusion equations, based on the Caputos time fractional derivative. Then this approximation equation leads the corresponding system of linear equation, which is large scale and sparse. Due to the characteristics of the coefficient matrix, we use the Accelerated Over-Relaxation (AOR) iterative method for solving the generated linear system. One example of the problem is presented to illustrate the effectiveness of AOR method. The numerical results of this study show that the proposed iterative method is superior compared with the existing one weighted parameter iterative method.

Path planning for mobile robot using 4EGSOR via Nine-Point Laplacian (4EGSOR9L) iterative method

paper presents an attempt to solve path planning problem for a mobile robot operating in indoor environment model using iterative numerical technique. It is based on the use of Laplaces Equation to compute the potential functions in the environment grid model of the robot. The proposed block iterative method, better known as Four Point-Explicit Group via Nine-Point Laplacian (4EGSOR9L), employs a finite- difference scheme to compute the potential functions to be used in generating smooth path between start and goal points. The simulation results demonstrate that the proposed 4EGSOR9L method performs faster than the previous methods in computing the potential functions of the environment model. Keywordspath planning; Four-Point Explicit Group SOR via Nine-Point Laplacian (4EG9LSOR); Laplaces equation.

Quarter-Sweep Arithmetic Mean Algorithm for water quality model

In the previous studies, approximate solutions of water quality model were calculated by half-sweep arithmetic mean (HSAM) and half-sweep geometric mean (HSGM) methods using the HSCN finite difference scheme. Based on the CN finite difference scheme, however, we investigate application of the quarter-sweep arithmetic mean (QSAM) method in assessing the water quality model. In this paper, the formulation of the FSAM, HSAM and QSAM needs will be presented. Finally, results on numerical experiments conducted validate that the QSAM method has been shown to be very fast as compared to the FSAM and HSAM methods.

A tale of two behaviour-based robots Mindstorms vs Technic

This paper describes our work to discover if LEGO Mindstorms can produce the behaviors needed for the intelligent sensing and control (ISC) practical. Two robots will be built; one using straight Mindstorms and one using Technic. These two robots will be built using similar hardware and software design. The aim is to make them as identical as possible so that direct comparison can be made. Additionally, another Mindstorms robot will be built, but enhanced to use two RCXs, which can communicate each other. All three robots then are to be competed each other in robot rugby game. Their performance in the game then is used to evaluate whether Mindstorms is suitable for ISC practical.

Application of SOR Iteration for Poisson Image Blending

Image blending is one of the important techniques in image processing. In this paper, a method based on solving the Poisson equation using Jacobi, Gauss-Seidel and SOR iterative methods is proposed. The aim is to compare and analyze the effectiveness of the three iterative methods in solving Poisson image blending problem. The evaluation criteria are based on the number of iterations and computational time to solve the Poisson equation. It is shown that SOR iterative method is more effective than the other two methods with a fewer number of iterations and requiring lesser computational time.