Perencanaan Jalur Dan Penghindaran Rintangan Dinamis Berbasis Rapidly-Exploring Random Tree Star dan Improved Artificial Potential Field Untuk Unmanned Surface Vehicle

Fayyadh, Fatih (2026) Perencanaan Jalur Dan Penghindaran Rintangan Dinamis Berbasis Rapidly-Exploring Random Tree Star dan Improved Artificial Potential Field Untuk Unmanned Surface Vehicle. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Navigasi otonom pada Unmanned Surface Vehicle (USV) memerlukan sistem yang mampu mencapai tujuan serta menghindari rintangan statis dan dinamis. RRT* dapat menghasilkan jalur global berdasarkan posisi rintangan statis, tetapi tidak merespons perubahan posisi rintangan dinamis selama USV bergerak. Penelitian ini bertujuan merancang, mengimplementasikan, dan mengevaluasi sistem navigasi terintegrasi pada USV LSS-01. Sistem menggunakan RRT* sebagai perencana jalur global, G2CBS sebagai penghalus jalur, ILOS sebagai pembentuk sudut heading acuan, Improved APF sebagai metode penghindaran rintangan dinamis, dan kontroler PID sebagai pengendali gerak USV. Pengujian dilakukan melalui empat skenario simulasi dan dua skenario implementasi di InfinITS Tekno Sains Park. Pada implementasi metode global, USV mencapai seluruh waypoint dan goal dalam 30,92 s dengan jarak tempuh 33,84 m dan jarak minimum 0,73 m terhadap rintangan statis. Pada implementasi metode global dan lokal, USV mencapai goal dalam 30,39 s dengan jarak tempuh 32,74 m dan jarak minimum 1,63 m terhadap rintangan statis. Pada simulasi, seluruh skenario berhasil mencapai goal tanpa tabrakan. Improved APF aktif selama 10,10 sampai 10,60 s dan menghasilkan jarak minimum 0,76 sampai 1,48 m terhadap rintangan dinamis. Selisih waktu aktual terhadap waktu rencana sebesar 0,90 sampai 2,35 s masih berada dalam time window ±5,00 s. Hasil pengujian menunjukkan bahwa integrasi RRT* dan Improved APF dapat diterapkan pada USV LSS-01 sebagai dasar pengembangan sistem navigasi yang lebih aman dan adaptif.
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Autonomous navigation for an Unmanned Surface Vehicle (USV) requires a system capable of reaching the destination while avoiding static and dynamic obstacles. RRT* can generate a global path based on known static-obstacle positions, but it cannot directly respond to changes in dynamic-obstacle positions while the USV is moving. This study aims to design, implement, and evaluate an integrated navigation system on the LSS-01 USV. The system uses RRT* for global path planning, G2CBS for path smoothing, ILOS for generating the heading reference, Improved APF for dynamic-obstacle avoidance, and PID controllers for controlling USV motion. The system was evaluated through four simulation scenarios and two implementation scenarios at InfinITS Tekno Sains Park. In the global-method implementation, the USV reached all waypoints and the goal in 30.92 s, traveled 33.84 m, and maintained a minimum static-obstacle distance of 0.73 m. In the global and local method implementation, the USV reached the goal in 30.39 s, traveled 32.74 m, and maintained a minimum static-obstacle distance of 1.63 m. In the simulations, all scenarios reached the goal without collision. Improved APF was active for 10.10 to 10.60 s and maintained minimum distances of 0.76 to 1.48 m from the dynamic obstacles. The differences between the actual and planned travel times ranged from 0.90 to 2.35 s and remained within the ±5.00 s time window. The results show that the integration of RRT* and Improved APF can be implemented on the LSS-01 USV as a basis for developing a safer and more adaptive navigation system.

Item Type: Thesis (Other)
Uncontrolled Keywords: implementasi USV, Improved APF, RRT*, penghindaran rintangan, navigasi otonom, USV implementation, Improved APF, RRT*, obstacle avoidance, autonomous navigation
Subjects: H Social Sciences > HE Transportation and Communications > HE336.R68 Route choice
T Technology > TJ Mechanical engineering and machinery > TJ212 Control engineering systems. Automatic machinery (General)
T Technology > TJ Mechanical engineering and machinery > TJ213 Automatic control.
T Technology > TJ Mechanical engineering and machinery > TJ223 PID controllers
T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL152.8 Vehicles, Remotely piloted. Autonomous vehicles.
T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL798.N3 Global Positioning System.
V Naval Science > VK > VK555 Navigation.
V Naval Science > VM Naval architecture. Shipbuilding. Marine engineering > VM365 Remote submersibles. Autonomous vehicles.
Divisions: Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User: Fatih Fayyadh
Date Deposited: 27 Jul 2026 01:54
Last Modified: 27 Jul 2026 01:54
URI: http://repository.its.ac.id/id/eprint/137741

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