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All Journal ComEngApp : Computer Engineering and Applications Journal Teliska Bulletin of Electrical Engineering and Informatics Proceeding of the Electrical Engineering Computer Science and Informatics Sinergi Annual Research Seminar Proceeding of the Electrical Engineering Computer Science and Informatics VOLT : Jurnal Ilmiah Pendidikan Teknik Elektro Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control Journal of Applied Smart Electrical Network and System (JASENS) Aptekmas : Jurnal Pengabdian Kepada Masyarakat

Yurni Oktarina

Politeknik Negeri Sriwijaya

Author-ID : 336990

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Published : 27 Documents Claim Missing Document

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Articles

Title

Object Following Design for a Mobile Robot using Neural Network Neta Larasati; Tresna Dewi; Yurni Oktarina
Computer Engineering and Applications Journal Vol 6 No 1 (2017)
Publisher : Universitas Sriwijaya

Deciding the best method for robot navigation is the most important tasks in mobile robot design, defined as the robot's ability to reach the target or/and move around its environment safely using the installed sensors and/or predefined map. To achieve this objective, wall or object detection can be considered. It is common to derive kinematics and dynamics to design the controls system of the robot, however by giving intelligence system to the robot, the control system will provide better performance for robot navigation. One of the most applied artificial intelligence is neural networks, a good approach for sensors of mobile robot system that is difficult to be modeled with an accurate mathematical equations. Mostly discussed basic navigation of a mobile robot is wall following. Wall following robot has been used for many application not only in industrial as a transport robot but also in domestic or hospital. Two behaviors are designed in this paper, wall following and object following. Object following behavior is developed from wall following by utilizing data from 4 installed distance sensors. The leader robot as the target for the follower robot, therefore the follower robot will keep on trying reaching for the leader in a safe distance. The novelty of this research is in the sense of the simplicity of proposed method. The feasibility of our proposed design is proven by simulation where all the results shows the effectiveness of the proposed method.

BLOB Analysis for Fruit Recognition and Detection Muhammad Dede Yusuf; RD Kusumanto; Yurni Oktarina; Tresna Dewi; Pola Risma
Computer Engineering and Applications Journal Vol 7 No 1 (2018)
Publisher : Universitas Sriwijaya

Robot application in agriculture can ease the farming process, especially as the harvesting robot for seasonal fruit that is available in a short time. The addition of "eye" as the image sensor is an important feature for a harvesting robot. Thanks to the increment of technology, the camera is getting smaller with better performance, and lower prices. The cheap sensors and components make the creation of cheap and effective robot possible. Image processing is necessary for object detection, and open source software is available now for this purpose. This paper proposes BLOB analysis for object detection of 5 fruits with different shapes and colors. The simulation results show that the proposed method is effective for object detection regardless the shapes, colors, and noises.

Neural Network Controller Application on a Visual based Object Tracking and Following Robot Pola Risma; Tresna Dewi; Yurni Oktarina; Yudi Wijanarko
Computer Engineering and Applications Journal Vol 8 No 1 (2019)
Publisher : Universitas Sriwijaya

Navigation is the main issue for autonomous mobile robot due to its mobility in an unstructured environment. The autonomous object tracking and following robot has been applied in many places such as transport robot in industry and hospital, and as an entertainment robot. This kind of image processing based navigation requires more resources for computational time, however microcontroller currently applied to a robot has limited memory. Therefore, effective image processing from a vision sensor and obstacle avoidances from distance sensors need to be processed efficiently. The application of neural network can be an alternative to get a faster trajectory generation. This paper proposes a simple image processing and combines image processing result with distance information to the obstacles from distance sensors. The combination is conducted by the neural network to get the effective control input for robot motion in navigating through its assigned environment. The robot is deployed in three different environmental setting to show the effectiveness of the proposed method. The experimental results show that the robot can navigate itself effectively within reasonable time periods.

Fuzzy-PID Controller Design of 4 DOF Industrial Arm Robot Manipulator Yurni Oktarina; Fradina Septiarini; Tresna Dewi; Pola Risma; Muhammad Nawawi
Computer Engineering and Applications Journal Vol 8 No 2 (2019)
Publisher : Universitas Sriwijaya

Arm robot manipulator is the most applied robot to substitute human labor in industries. Due to the importance of arm robot manipulator in manufacturing lines, the robustness and effective design are essential in building an arm robot. This paper presents the controller, mechanical, and motion designs of an arm robot manipulator. The fuzzy logic controller is employed to ensure the effectiveness in detecting the target object. PID controller is designed to enhance the smooth and stability of robot motion. The simulation of how the robot move inside its workspace was conducted using RSTX toolbox in SciLab. The motion is generated by deriving Denavit-Hartenberg parameters of the mechanical design. The result shows the effective design of Fuzzy-PID controller and mechanical design of a pick and places arm robot manipulator.

Finger Cue for Mobile Robot Motion Control Tresna Dewi; Amperawan Amperawan; Pola Risma; Yurni Oktarina; Dicky Astra Yudha
Computer Engineering and Applications Journal Vol 9 No 1 (2020)
Publisher : Universitas Sriwijaya

The current technology enables automation using a robot to help or substitute humans in industry and domestic applications. This robot invasion to human life emerges a new requirement to set a method of communication between a human and a robot. One of the oldest languages is finger gesture, and this is easy to be applied method by implementing image detection that connected to the actuators of the robot to respond to human orders. This paper presents a method to navigate robots based on human fingers cue, including "Forward," "Backward," "Turn right," "Turn left," and "Stop" to generate the forward, backward, turn right, turn left, and stop motion. The finger detection is facilitated by a camera module (NFR2401L) with the image plane of 640 x 480 and 30 fps speed. The detection in coordinates x <43 and y <100, robot moves forward, in x <29 and y <100-coordinates , robot turns left, and in x <19 and y <100-coordinates , robot turns right. The experiment was conducted to show the effectiveness of the proposed method, and to some extent robot can follow human cues to navigate in its assigned location.

The Concept of Automatic Transport System Utilizing Weight Sensor Yurni Oktarina; Tresna Dewi; Pola Risma
Computer Engineering and Applications Journal Vol 9 No 2 (2020)
Publisher : Universitas Sriwijaya

The current pandemic situation insists that people find a way to create a physical distance, limiting the number of people in a closed room. The human need for commuting has led to the idea of an automatic transport system that can transport people and goods without the assistance of a driver. This idea can lead to a new "normal" and reduced cost of manufacturing in the industry. The paper discussed the concept of an automatic transport system using a weight sensor. An automatic vehicle is designed to transport loads of different packages and be allocated automatically based on the weight of the package. The system is designed to be as simple as possible to increase the scope for implementation.

Simulation Design of Artificial Intelligence Controlled Goods Transport Robot Yurni Oktarina; Destri Zumar Sastiani; Tresna Dewi
Computer Engineering and Applications Journal Vol 11 No 2 (2022)
Publisher : Universitas Sriwijaya

Technological advances enable scientists and researchers to develop more automated systems for life's convenience. Transportation is among those conveniences needed in daily activities, including warehouses. The easy-to-build and straightforward transport robot are desired to ease human workers' working conditions. The application of artificial intelligence (AI), Fuzzy Logic Controller, and Neural Network ensures the robot is able to finish assigned tasks better and faster. This paper shows the concept design of an AI-controlled good transport robot applied in the warehouse. The design is made as fast and straightforward forward possible, and the feasibility of the proposed method is proven by simulation in Scilab FLT and Neuroph.

Co-Authors Amperawan Amperawan Anggraini, Citra Aulia Ratna Juwita Citra Anggraini Dadi Setiadi Destri Zumar Sastiani Dewi, Tresna Dicky Astra Yudha Edo Triyandi Evelina Ginting Fradina Septiarini Husni, Nyayu Latifah Lin Prasetyani M. Nawawi Mayastri Devana Muhammad Dede Yusuf Muhammad Nawawi Muhammad Nouval Daniesar Muhammad Ridho Kenawas Muhammad Taufik Roseno Mulya, Zarqa Muslikhin Muslikhin Muslikhin Muslikhin Nawawi, M. Neta Larasati Pola Risma Prasetyani, Lin Pratama, Yudha Wira Putri Repina Kesuma RD Kusumanto Rinaldi Rinaldi Ronald Sukwadi SELAMET MUSLIMIN Siproni Umar Siti Afiyah Qatrunnada Sri Rezki Artini Tresna Dewi Tresna Dewi Tresna Dewi Tulak, Windy Gafrila Wahju, Marsellinus Bachtiar Windy Gafrila Tulak Yudha Wira Pratama Yudi Wijanarko Zarqa Mulya

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