Harahap, Faadhil Inayatur Rahman (2025) Perencanaan Lintasan USV Untuk Meminimumkan Waktu Tempuh Menggunakan Algoritma Rapidly-Exploring Random Tree* dan Dynamic Window Algorithm. Other thesis, Institut Teknologi Sepuluh Nopember Surabaya.
![[thumbnail of 5022211102-Undergraduate_Thesis.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
5022211102-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (4MB) | Request a copy |
Abstract
Unmanned Surface Vehicle (USV) merupakan kendaraan laut tak berawak yang semakin berkembang untuk berbagai aplikasi, seperti operasi militer, penelitian maritim, dan transportasi otonom. Seiring dengan meningkatnya kebutuhan transportasi laut yang efisien, diperlukan sistem navigasi yang mampu merencanakan lintasan secara optimal untuk meminimalkan waktu tempuh. Tantangan utama dalam perencanaan lintasan USV adalah memastikan jalur yang dipilih tidak hanya efisien tetapi juga mampu beradaptasi dengan kondisi lingkungan yang dinamis, termasuk rintangan statis maupun bergerak. Penelitian ini mengusulkan kombinasi algoritma Rapidly exploring Random Tree* (RRT*) dan Dynamic Window Approach (DWA) untuk meningkatkan efisiensi perjalanan USV. Algoritma RRT* digunakan sebagai global path planner untuk menghasilkan lintasan optimal berdasarkan peta lingkungan, sedangkan DWA berfungsi sebagai local path planner untuk memastikan navigasi yang adaptif terhadap perubahan lingkungan secara real-time. Pendekatan ini bertujuan untuk mengatasi keterbatasan masing-masing algoritma, di mana RRT* unggul dalam pencarian jalur optimal tetapi kurang responsif terhadap rintangan dinamis, sementara DWA mampu menghindari rintangan tetapi berisiko jatuh ke local optimum. Hasil simulasi menunjukkan bahwa kombinasi RRT* dan DWA dapat secara signifikan mengurangi waktu tempuh dibandingkan metode konvensional, sekaligus meningkatkan keamanan navigasi USV dalam lingkungan perairan yang kompleks. Dengan lintasan yang lebih efisien dan kemampuan adaptasi yang lebih baik terhadap kondisi perairan, metode ini memiliki potensi besar dalam mendukung pengembangan USV untuk berbagai kebutuhan maritim di Indonesia secara lebih efisien dan adaptif.
=================================================================================================================================
Unmanned Surface Vehicles (USVs) are increasingly developing unmanned marine vehicles for various applications, such as military operations, maritime research, and autonomous transportation. As the need for efficient marine transportation increases, a navigation system capable of optimally planning trajectories to minimize travel time is required. The main challenge in USV trajectory planning is to ensure the chosen path is not only efficient but also able to adapt to dynamic environmental conditions, including both static and moving obstacles. This research proposes a combination of Rapidly exploring Random Tree* (RRT*) and Dynamic Window Approach (DWA) algorithms to improve USV traveling efficiency. The RRT* algorithm is used as a global path planner to generate optimal trajectories based on the environment map, while the DWA serves as a local path planner to ensure adaptive navigation to real-time environmental changes. This approach aims to overcome the limitations of each algorithm, where RRT* excels in optimal path finding but is less responsive to dynamic obstacles, while DWA is able to avoid obstacles but risks falling into the local optimum. Simulation results show that the combination of RRT* and DWA can significantly reduce travel time compared to conventional methods, while improving the safety of USV navigation in complex water environments. With more efficient trajectories and better adaptability to water conditions, this method has great potential in supporting the development of USVs for various maritime needs in Indonesia more efficiently and adaptively.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Dynamic Window Algorithm, Rapidly exploring Random Tree* , Control, USV, Waktu Tempuh, Penghindaran Rintangan. ======================================================================================================================== Dynamic Window Algorithm, Rapidly exploring Random Tree*, Control, USV, Travel Time, Obstacle Avoidance. |
| Subjects: | T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL152.8 Vehicles, Remotely piloted. Autonomous vehicles. |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis |
| Depositing User: | Faadhil Inayatur Rahman Harahap |
| Date Deposited: | 25 Jul 2025 02:11 |
| Last Modified: | 25 Jul 2025 02:11 |
| URI: | http://repository.its.ac.id/id/eprint/121584 |
Actions (login required)
 |
View Item |