Rahman, Musthafa Khalil (2026) Implementasi Algoritma Theta* Untuk Perencanaan Jalur Global Dan Dynamic Window Approach (DWA) Untuk Jalur Lokal Pada Unmanned Surface Vehicle (USV). Other thesis, Institut Teknologi Sepuluh Nopember.
![[thumbnail of 5022221035-Undergraduate_Thesis.pdf]](http://repository.its.ac.id/style/images/fileicons/text.png) |
Text
5022221035-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (4MB) | Request a copy |
Abstract
Navigasi otonom pada Unmanned Surface Vehicle (USV) memerlukan perencanaan jalur yang efisien sekaligus kemampuan menghindari rintangan yang muncul secara real time. Pada penelitian ini diimplementasikan integrasi algoritma Theta* sebagai perencana jalur global dengan Dynamic Window Approach (DWA) sebagai perencana jalur lokal pada USV LSS-01. Theta* dipilih karena kemampuan any angle yang menghasilkan jalur lebih halus dan natural, sedangkan DWA berperan menghindari rintangan secara reaktif. Sistem dirancang dalam arsitektur berlapis Theta* dan DWA, divalidasi melalui simulasi MATLAB pada empat variasi skenario, kemudian diimplementasikan pada USV LSS-01 menggunakan ROS Noetic dan diuji di Danau InfinITS ITS. Hasil simulasi menunjukkan bahwa Theta* menghasilkan jarak tempuh 50,84 m, kompetitif terhadap algoritma pembanding (Dijkstra 48,95 m; PRM 50,54 m; Bidirectional A* 51,92 m) dengan selisih di bawah 6%. Pengujian dengan DWA aktif berhasil mempertahankan keselamatan navigasi tanpa pelanggaran zona maupun tabrakan, sedangkan tanpa DWA sistem mengalami tabrakan terhadap rintangan dinamis. Pada implementasi lapangan, sistem berhasil mencapai seluruh waypoint serta menghindari rintangan statis maupun dinamis dengan jarak minimum di atas radius aman. Penelitian ini membuktikan bahwa integrasi Theta* dan DWA mampu menghasilkan navigasi USV yang efisien, adaptif, dan aman.
========================================================================================================================================
Autonomous navigation of an Unmanned Surface Vehicle (USV) requires efficient path planning together with the ability to avoid obstacles in real time. This research implements the integration of the Theta* algorithm as a global path planner with the Dynamic Window Approach (DWA) as a local path planner on the USV LSS-01. Theta* was selected for its any-angle capability that produces smoother and more natural paths, while DWA reactively avoids obstacles. The system was designed in a layered Theta* and DWA architecture, validated through MATLAB simulation across four scenario variations, and then implemented on the USV LSS-01 using ROS Noetic and tested at Danau InfinITS ITS. Simulation results show that Theta* produced a path length of 50.84 m, competitive against the comparison algorithms (Dijkstra 48.95 m; PRM 50.54 m; Bidirectional A* 51.92 m), with a difference of less than 6%. Testing with DWA active successfully maintained navigation safety without any zone violations or collisions, whereas without DWA the system collided with a dynamic obstacle. In the field implementation, the system successfully reached all waypoints and avoided both static and dynamic obstacles with minimum distances above the safe radius. This research demonstrates that the integration of Theta* and DWA is capable of producing efficient, adaptive, and safe USV navigation.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Dynamic Window Approach, Navigasi Otonom, Algoritma Theta*, Unmanned Surface Vehicle, USV LSS-01, Autonomous Navigation, Dynamic Window Approach, Theta* Algorithm |
| 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: | Musthafa Khalil Rahman |
| Date Deposited: | 24 Jul 2026 01:54 |
| Last Modified: | 24 Jul 2026 01:54 |
| URI: | http://repository.its.ac.id/id/eprint/136780 |
Actions (login required)
 |
View Item |