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All Journal Jurnal Teknik ITS IPTEK Journal of Proceedings Series TELKOMNIKA (Telecommunication Computing Electronics and Control) Jurnal Ilmiah Kursor International Journal of Advances in Intelligent Informatics JURNAL NASIONAL TEKNIK ELEKTRO Jurnal Teknologi dan Sistem Komputer Kinetik: Game Technology, Information System, Computer Network, Computing, Electronics, and Control APPROACH: Jurnal Teknologi Penerbangan JAVA Journal of Electrical and Electronics Engineering JAREE (Journal on Advanced Research in Electrical Engineering) International Journal of Robotics and Control Systems Jurnal Nasional Teknik Elektro dan Teknologi Informasi Sewagati
Ronny Mardiyanto, Ronny
Departemen Teknik Elektro - ITS, Surabaya
Aerospace Engineering Arts Humanities Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Education Electrical & Electronics Engineering Energy Engineering Languange, Linguistic, Communication & Media Public Health Social Sciences Other

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Journal : Jurnal Nasional Teknik Elektro dan Teknologi Informasi

 1 
Autopilot Pesawat Tanpa Awak Menggunakan Algoritme Genetika untuk Menghilangkan Blank Spot Ronny Mardiyanto; Muhammad Ichlasul Salik; Djoko Purwanto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 11 No 1: Februari 2022
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1669.33 KB) | DOI: 10.22146/jnteti.v11i1.2492

Abstract

This paper presents the autopilot of unmanned aerial vehicles (UAV) with the ability to minimize blank spots on aerial mapping using the genetic algorithm. The purpose of the developed autopilot is to accelerate the times required for aerial mapping and save battery consumption. Faster time in conducting aerial mapping saves operational costs, saves battery consumption, and reduces UAV maintenance costs. The proposed autopilot has the ability to analyze blank spots from aerial shots and optimize flight routes for re-photography. The genetic algorithm was applied to obtain the shortest distance, which was done to save battery consumption and flight time. When developing the autopilot, the operator would manually set the flight route, then the aircraft would fly according to that route. The unstable wind factor has caused a shift in the flight route, which correspondingly caused blank spots. After all flight routes were traversed, the system developed would analyze the location of the blank spots. The new flight route was calculated using the genetic algorithm to determine the shortest distance from all the blank spot locations. The system developed consisted of a UAV equipped with autopilot and a ground control station (GCS). At the time of flight, the UAV would send the coordinates of the path traversed to the GCS to calculate the blank spot analysis. After the flight mission has been completed, the GCS would create a new route and send it to the UAV. The test carried out was an aircraft with a height of 120m using a 4S 4,200 mAh 25C lipo battery, and the percentage of throttle when flying straight was 30%. The results obtained are that the developed autopilot saves 46.4% of the time and saves 41.18% of battery capacity compared to conventional autopilots.
Peningkatan Akurasi Adaptive Monte Carlo Localization Menggunakan Convolutional Neural Network Riza Agung Firmansyah; Tri Arief Sardjono; Ronny Mardiyanto
Jurnal Nasional Teknik Elektro dan Teknologi Informasi Vol 12 No 3: Agustus 2023
Publisher : Departemen Teknik Elektro dan Teknologi Informasi, Fakultas Teknik, Universitas Gadjah Mada

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.22146/jnteti.v12i3.7432

Abstract

This paper explains the increase in localization system accuracy of the adaptive Monte Carlo localization (AMCL) in robots utilizing a convolutional neural network (CNN). The localization system in robots is defined as the position recognition process of robots within their working environment. This system is essential as it allows robots to navigate and map efficiently and accurately. Without appropriate localization, robots cannot operate effectively and can encounter troubles such as losing direction or bumping into objects. AMCL is a popular localization system and is widely applied in robots. This method utilizes the changes in the robots’ position and light detection and ranging (LiDAR) sensor reading as input. Reading of robot position changes is susceptible to error due to slips or wheel deformations. The inaccuracy of reading the robots’ position change results in the inaccuracy of the robots’ position prediction by AMCL, so improvements are required. Novelty in this paper includes providing compensation values from AMCL results for the error to be small. These compensation values were obtained from the CNN training results; hence, the proposed method was dubbed AMCL+CNN. Inputs given to the CNN were the changes in wheel odometry values and distance reading by the LiDAR sensor. CNN outputs were compared to the target data in the form of the robots’ actual position from observation results. Network training was conducted for as many as 200 epochs to achieve the lowest validation loss. Testing was done on a robot installed with a robot operating system (ROS). Training and testing datasets were obtained from rosbag data when the robot traversed the testing area. In straight and turn scenarios, obtained AMCL+CNN algorithms had fewer errors than the regular AMCL and Monte Carlo localization (MCL). Results obtained are also superior in terms of positional error metrics when compared to several other comparison methods.
Co-Authors Aang Kisnu Darmawan Aang Kisnu Darmawan Ahmad Fahriannur Akbar Faiz Andri Suhartono Andri, Kuntoro Boga Andrian, Muhammad Yunus Aryani, Ni Ketut Astria Nur Irfansyah Badrut Tamam Budiman, Fajar D C Riawan D Fahmi Dedet Candra Riawan Devy Kuswidiastuti Diah Kusumawati, Diah Djoko Purwanto Fahad Al Hazmi Feby Agung Pamuji Firmansyah, Riza Agung Gangsarestu, Muhammad Soleh Haris Hariza Ekarinda Heri Suryoatmojo Hoiriyah Hoiriyah, . Indra Dilianto Iwan Santosa Iwan Santosa Iwan Vanany Joko Subur K B Adam Kohei Arai Meilana Siswanto Mochamad Ashari Muhammad Attamimi Muhammad Ichlasul Salik Muhammad Qomaruz Zaman Muhammad Rivai Muhammad Saiful Hak Muhammad Yunus Andrian Muharom, Syahri Niniek Fajar Puspita, Niniek Fajar Ontoseno Penangsang Parama, Armand Dvi Prasetiyono Hari Mukti Putra, Karisma Trinanda Rahmad Hidayat Rifyal Rachmat Riza Agung Rony Seto Wibowo Rudy Dikairono Ruth Johana Hutagalung S Hidayat Setijadi, Eko Suwito Suwito Suwito Suwito Totok Mujiono, Totok Tri Arief Sardjono Uroidhi, Ali Winarsih, Wiwik Heny Yunardi, Riky Tri Zaman, Muhammad Qomaruz