Implementasi Perencanaan Lintasan Pada Unmanned Surface Vehicle (USV) Menggunakan Algoritma Bidirectional A* Dan Artificial Potential Field

Erismayana, Kaira Alifian (2026) Implementasi Perencanaan Lintasan Pada Unmanned Surface Vehicle (USV) Menggunakan Algoritma Bidirectional A* Dan Artificial Potential Field. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Indonesia memiliki wilayah perairan yang luas sehingga membutuhkan teknologi navigasi otonom untuk mendukung berbagai aktivitas kelautan. Penelitian ini mengimplementasikan sistem perencanaan lintasan pada Unmanned Surface Vehicle (USV) dengan menggabungkan Bidirectional A* sebagai global path planning dan Artificial Potential Field (APF) sebagai local path planning. Lintasan global diperhalus menggunakan G2 Continuous Bezier Spiral (G2CBS), kemudian diikuti oleh sistem ILOS Guidance, PID Speed Controller, dan Fuzzy PID Heading Controller. Pengujian dilakukan melalui simulasi MATLAB menggunakan model USV 4-DOF dan implementasi pada USV LSS-01. Pada simulasi global path planning, USV mencapai tujuan tanpa memotong enam Obstacle statis dalam waktu 37,6 s, dengan panjang lintasan referensi 52,423 m dan jarak aktual 52,297 m. Pada skenario Obstacle dinamis, sistem tanpa APF mengalami collision, sedangkan penggunaan APF memungkinkan USV mencapai tujuan tanpa tabrakan dalam waktu 37,9 s dengan jarak aktual 52,771 m. Pada implementasi global path planning, seluruh waypoint dicapai dalam waktu 49,27 s dengan panjang lintasan referensi 41,662 m, jarak aktual 41,938 m, mean cross-track error 1,521 m, dan nilai maksimum 3,560 m. Pada implementasi global dan local path planning, seluruh waypoint dicapai dalam waktu 51,47 s dengan panjang lintasan referensi 43,57 m, jarak aktual 40,60 m, mean cross-track error 2,017 m, dan nilai maksimum 4,442 m. Hasil pengujian menunjukkan bahwa Bidirectional A* mampu membentuk lintasan global, G2CBS memperhalus perubahan arah, dan APF memberikan koreksi lintasan untuk menghindari Obstacle dinamis
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Indonesia has vast water areas, creating a need for autonomous navigation technology to support various maritime activities. This study implements a path-planning system for an Unmanned Surface Vehicle (USV) by integrating Bidirectional A* as the global path planner and Artificial Potential Field (APF) as the local path planner. The global path is smoothed using the G2 Continuous Bezier Spiral (G2CBS) method and followed using ILOS Guidance, a PID Speed Controller, and a Fuzzy PID Heading Controller. Testing was conducted through MATLAB simulations using a 4-DOF USV model and field implementation on the LSS-01 USV. In the global path-planning simulation, the USV reached the goal without intersecting six static Obstacles in 37.6 s, with a reference path length of 52.423 m and an actual travel distance of 52.297 m. In the dynamic-Obstacle scenario, the system without APF experienced a collision, whereas the use of APF enabled the USV to reach the goal without collision in 37.9 s, with an actual travel distance of 52.771 m. In the global path-planning implementation, all waypoints were reached in 49.27 s, with a reference path length of 41.662 m, an actual travel distance of 41.938 m, a mean cross track error of 1.521 m, and a maximum value of 3.560 m. In the combined global and local path planning implementation, all waypoints were reached in 51.47 s, with a reference path length of 43.57 m, an actual travel distance of 40.60 m, a mean cross-track error of 2.017 m, and a maximum value of 4.442 m. The results show that Bidirectional A* successfully generates the global path, G2CBS smooths directional changes, and APF provides path corrections to avoid dynamic Obstacles.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Unmanned Surface Vehicle, Bidirectional A*, Artificial Potential Field, perencanaan jalur, penghindaran rintangan. Unmanned Surface Vehicle, Bidirectional A*, Artificial Potential Field, Obstacle avoidance, path planning.
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:	Kaira Alifian Erismayana
Date Deposited:	28 Jul 2026 01:33
Last Modified:	05 Aug 2026 05:29
URI:	http://repository.its.ac.id/id/eprint/138179

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