Faqih, Muhamad Fahmi (2026) Formasi Leader-Follower dan Perencanaan Lintasan Pada Nonholonomic Mobile Robot Menggunakan Algoritma RRT-APF Fusion. Other thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Pemanfaatan Nonholonomic Mobile Robot (NMR) dalam misi eksplorasi otonom menuntut sistem navigasi cerdas yang mampu beradaptasi terhadap lingkungan yang kompleks dan berubah-ubah. Tantangan utama dalam navigasi ini adalah merancang perencanaan lintasan yang aman di tengah keberadaan rintangan statis maupun rintangan dinamis yang bergerak secara real-time. Penelitian ini mengusulkan integrasi metode Rapidly-exploring Random Tree (RRT) dan Artificial Potential Field (APF), atau disebut RRT-APF Fusion, sebagai solusi untuk perencanaan lintasan, serta menerapkan skema Leader-Follower untuk kontrol formasi pada tiga agen NMR. Algoritma RRT-APF Fusion dirancang untuk menutupi kelemahan masing-masing metode dasar, yaitu efisiensi pencarian lintasan dan kerentanan terhadap local minimum. Hasil simulasi menunjukkan bahwa algoritma usulan tidak hanya mampu mengatasi local minimum, tetapi juga responsif dalam melakukan penghindaran terhadap rintangan dinamis yang muncul di sepanjang lintasan. Meskipun rata-rata waktu komputasi meningkat menjadi 4,336 detik dibandingkan metode RRT murni (1,882 detik), metode ini menawarkan keunggulan signifikan dalam aspek keselamatan dan adaptabilitas lingkungan. Evaluasi pada sistem multi-agen menunjukkan bahwa algoritma kontrol formasi mampu menjaga kohesi grup dengan total rata-rata galat posisi sebesar 0,758 meter. Nilai ini mengindikasikan bahwa formasi dapat dipertahankan dengan cukup baik meskipun robot harus melakukan manuver untuk menghindari rintangan yang bergerak.
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The utilization of Nonholonomic Mobile Robots (NMR) in autonomous exploration missions requires an intelligent navigation system capable of adapting to complex and dynamic environments. A primary challenge in this domain is designing safe path planning strategies in the presence of both static and real-time dynamic obstacles. This study proposes the integration of the Rapidly-exploring Random Tree (RRT) and Artificial Potential Field (APF) methods, termed RRT-APF Fusion, as a path planner solution. Additionally, a Leader-Follower scheme is implemented for formation control across three NMR agents. The RRT-APF Fusion method is designed to address the inherent limitations of the fundamental methods, specifically regarding path search efficiency and susceptibility to local minimum. Simulation results demonstrate that the proposed algorithm not only effectively overcomes local minima problems but also exhibits high responsiveness in avoiding dynamic obstacles that appear along the trajectory. Although the average computation time increased to 4.336 seconds compared to the pure RRT method (1.882 seconds), the proposed method offers significant advantages in terms of operational safety and environmental adaptability. Furthermore, evaluations of the multi-agent system indicate that the formation control algorithm successfully maintains group cohesion, yielding a total average position error of 0.758 meters. This value suggests that the formation is adequately maintained, even when the robots are required to execute maneuvers to evade moving obstacles.
| Item Type: | Thesis (Other) |
|---|---|
| Uncontrolled Keywords: | Nonholonomic Mobile Robot, RRT-APF Fusion, Leader-follower, Perencanaan Lintasan, Kontrol Formasi, Nonholonomic Mobile Robot, RRT-APF Fusion, Leader-follower, Path Planning, Formation Control. |
| Subjects: | T Technology > TJ Mechanical engineering and machinery > TJ211.415 Mobile robots 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: | Muhamad Fahmi Faqih |
| Date Deposited: | 22 Jan 2026 09:24 |
| Last Modified: | 22 Jan 2026 09:24 |
| URI: | http://repository.its.ac.id/id/eprint/130113 |
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