Awang Hendrianto Pratomo
National University of Malaysia
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Publication
Featured researches published by Awang Hendrianto Pratomo.
international conference on electrical engineering and informatics | 2009
Awang Hendrianto Pratomo; Mohd Shanudin Zakaria; Anton Satria Prabuwono
Camera calibration and image processing is the most important factor in computer vision. Some of the techniques that are applied in the process of calibration are linier, technical and non technical linier with two stages. Calibration techniques can be implemented, for example in the Autonomous Robotic Soccer. The process of calibration is one of the key factors of success in robotic soccer game. Currently, the team succeeded in doing with the camera calibration is a good team who will be able to win the match.
14th FIRA RoboWorld Congress on Next Wave in Robotics, FIRA 2011 | 2011
Awang Hendrianto Pratomo; Anton Satria Prabuwono; Siti Norul Huda Sheikh Abdullah; Mohamad Shanudin Zakaria
In this paper, we create a passing, obstacle avoiding and shooting strategy for robotic soccer coordination. Based on a predefined-scenario in a robotic soccer game, we simulate a mini case study which involves two robots and a ball. We modify role, act and behavior method to meet the game requirements. About 61% of the testing achieved the shooting of a goal by manipulating and redesigning the strategy. The shortest goal shooting time was about 5 seconds. We hope to improve this initial strategy in the future.
Revista De Informática Teórica E Aplicada | 2015
Awang Hendrianto Pratomo; Mohamad Shanudin Zakaria; Mohammad Faidzul Nasrudin; Anton Satria Prabuwono; Choong Yeun Liong; Izwan Azmi
The MirosSot and the AndroSot soccer robots have the ability to recognize, and navigate within, their environments without human intervention. An overhead global camera, usually at a fixed position, is used for the robot’s vision. Because of the lens distortion, images obtained from the camera do not accurately represent the robot’s environment. The distortions affect the coordinates. A technique to calibrate the camera is required to transform the skewed coordinates of the objects in the image to the physical coordinates, which define their real-world position. In this study, a method is proposed for camera calibration using an artificial neural network (ANN) in a two-step process. First, ANN was used to select the camera height and the lens focal lengths for high accuracy. Second, ANN was used to map a coordinate transformation from the camera coordinates to the physical coordinates. During the learning process, the weight of each node in the ANN model changed until the best architecture is reached. The experiments thus resulted in an optimum ANN architecture of 2×4×25×2. The accuracy and efficiency of the camera calibration method were obtained by relearning using the ANN whenever changes to the environmental occurred. Relearning was done using the new input data set for each respective environmental change. Based on our experiments, the average transformation error of the calibration method, using many types of camera, camera positions, camera heights, lens sizes, and focal lengths, was 0.18283 cm.
16th FIRA RoboWorld Congress, FIRA 2013 | 2013
Awang Hendrianto Pratomo; Mohamad Shanudin Zakaria; Anton Satria Prabuwono; Choong Yeun Liong
Vision system will make robotic system has the ability to see and modeled the real world objects. There are many factors that can affect the process of robot vision such as lens distortion, camera position which is not always at the center on the robot environment, the robot and other objects movement. In this research, we design an architecture using neural network to apply for global vision in autonomous mobile robot engine. The scheme is concerning to the development of camera calibration technique using neural network for precise and accurate position and orientation the robots. Its goal is to develop a robust camera calibration technique, to estimate the parameters of a transformation in the real world coordinate into image coordinate systems in autonomous mobile robots. The objective of our research is to propose and develop calibration techniques in a global overhead vision system for autonomous mobile robots. It aims to map and identify the identity of a robot in various conditions and camera position. Artificial Neural Network method (ANN) has been proposed as a method for solving coordinates transformation problems for non-linear lens distortion. The coordinate transformation was tested by placing cameras at various heights and setting camera angle with various zoom and focal length values.
Journal of Computer Science | 2010
Awang Hendrianto Pratomo; Anton Satria Prabuwono; Mohd Shanudin Zakaria; Khairuddin Omar; Jan Nordin; Shahnorbanun Sahran; Siti Norul Huda Sheikh Abdullah; Anton Heryanto
Journal of Applied Sciences | 2011
Awang Hendrianto Pratomo; Anton Satria Prabuwono; Siti Norul Huda Sheikh Abdullah; Mohd Shanudin Zakaria; Mohammad Faidzul Nasrudin; Khairuddin Omar; Shahnorbanun Sahran; M. J. Nordin
Archive | 2009
Awang Hendrianto Pratomo; Mohd Shanudin Zakaria; Anton Satria Prabuwono; Khairuddin Omar
Seminar Nasional Informatika (SEMNASIF) | 2015
Awang Hendrianto Pratomo; Mohd Shanudin Zakaria; Anton Satria Prabuwono
Seminar Nasional Informatika (SEMNASIF) | 2015
Awang Hendrianto Pratomo; Mohd Shanudin Zakaria; Anton Satria Prabuwono; Khairuddin Omar; Siti Norul Huda Syeikh Abdullah
Seminar Nasional Informatika (SEMNASIF) | 2011
Awang Hendrianto Pratomo; Anton Satria Prabuwono; Siti Norul Huda Seikh Abdullah; Mohd Shanudin Zakaria; Kahiruddin Omar