Implementasi Perencanaan Lintasan Unamanned Surface Vehicle (USV) Menggunakan Algoritma Improved Ant Colony dan Velocity Obstacle

Reihan, Muhammad (2026) Implementasi Perencanaan Lintasan Unamanned Surface Vehicle (USV) Menggunakan Algoritma Improved Ant Colony dan Velocity Obstacle. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Unmanned Surface Vehicle (USV) membutuhkan sistem navigasi otonom yang mampu menghasilkan jalur yang aman dan efisien sekaligus menghindari rintangan, baik yang diam maupun yang bergerak, di lingkungan perairan. Penelitian ini merancang dan mengevaluasi sistem navigasi otonom dua tingkat untuk USV yang memadukan perencanaan jalur global berbasis Improved Ant Colony Optimization (IACO) dengan penghindaran rintangan dinamis berbasis Velocity Obstacle (VO). Sistem ini dilengkapi pemanduan Integral Line-of-Sight (ILOS) dan kontroler PID untuk menjaga kestabilan gerak USV selama mengikuti lintasan yang direncanakan. Kinerja sistem diuji melalui simulasi pada skenario rintangan statis maupun gabungan rintangan statis dan dinamis dengan gangguan lingkungan yang aktif. Hasil pengujian menunjukkan bahwa USV mampu mencapai titik tujuan tanpa tabrakan pada seluruh skenario, dengan lintasan yang halus serta penambahan waktu tempuh yang kecil ketika harus menghindari rintangan yang bergerak. Secara keseluruhan, arsitektur IACO+VO+PID terbukti mampu menghasilkan navigasi yang aman, halus, dan efisien pada model USV yang realistis.
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An Unmanned Surface Vehicle (USV) requires an autonomous navigation system capable of generating safe and efficient paths while avoiding both stationary and moving obstacles in aquatic environments. This research designs and evaluates a two-level autonomous navigation system for a USV that combines global path planning based on Improved Ant Colony Optimization (IACO) with dynamic obstacle avoidance based on the Velocity Obstacle (VO) method. The system is supported by Integral Line-of-Sight (ILOS) guidance and PID controllers to maintain the stability of the USV motion while following the planned path. The system performance was evaluated through simulations involving static as well as combined static and dynamic obstacle scenarios under active environmental disturbances. The results show that the USV is able to reach its destination without collisions across all scenarios, producing smooth trajectories with only a small increase in travel time when avoiding moving obstacles. Overall, the IACO+VO+PID architecture proves capable of producing safe, smooth, and efficient navigation on a realistic USV model.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Improved Ant Colony Optimization, Path Planning, PID, Unmanned Surface Vehicle, Velocity Obstacle.
Subjects:	Q Science > Q Science (General) > Q337.3 Swarm intelligence T Technology > TJ Mechanical engineering and machinery > TJ223 PID controllers 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:	Muhammad Reihan
Date Deposited:	23 Jul 2026 08:30
Last Modified:	23 Jul 2026 08:30
URI:	http://repository.its.ac.id/id/eprint/136531

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