Majid, Muhammad Aqil Rayhan (2026) Implementasi Multi-Sensor Untuk Sistem Obstacle Avoidance pada Mobile Robot. Masters thesis, Institut Teknologi Sepuluh Nopember.
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Abstract
Navigasi mobile robot tetap menjadi tantangan dalam lingkungan yang dinamis dan tidak terstruktur. Penelitian ini mengusulkan metode Adaptive Beta-Weighted Force Field untuk penghindaran halangan secara real-time, di mana koefisien gaya repulsif beradaptasi secara kontinu berdasarkan jarak obstacle dan klasifikasi jenis obstacle. Berbeda dengan force field konvensional yang menggunakan bobot tetap, metode ini memodulasi penguatan repulsif secara proporsional terhadap kedekatan dan mobilitas setiap obstacle, sehingga mobile robot bisa merespons pada jarak jauh dan bereaksi cepat pada penghindaran jarak dekat. Tiga konfigurasi dievaluasi melalui simulasi pada lingkungan obstacle identik (statis dan dinamis) dengan global planner A-star: baseline bobot tetap terdiferensiasi, kontrol bobot tetap seragam, dan metode bobot adaptif yang diusulkan. Metode adaptif terbukti mencapai waktu navigasi tercepat sekaligus perilaku gaya paling stabil dan mulus, dengan variabilitas gaya avoidance berkurang substansial dibandingkan kedua baseline tanpa mengorbankan efisiensi jalur. Secara kuantitatif, metode adaptif mencapai waktu navigasi 17,20 detik, gaya avoidance rata-rata 2,848 N, dan standar deviasi gaya 4,361 N merepresentasikan pengurangan waktu tempuh 22% dan pengurangan variabilitas gaya 74% dibandingkan baseline bobot tetap, dengan efisiensi path following 96,6%.
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Mobile robot navigation remains a challenge in dynamic and unstructured environments. This research proposes an Adaptive Beta-Weighted Force Field method for real-time obstacle avoidance, in which the repulsive force coefficient adapts continuously based on obstacle distance and obstacle type classification. Unlike conventional force fields that employ fixed weights, this method modulates the repulsive gain proportionally to the proximity and mobility of each obstacle, enabling the mobile robot to respond at long range and react rapidly during close-range avoidance. Three configurations were evaluated through simulations in identical obstacle environments (both static and dynamic) using an A-star global planner: a differentiated fixed-weight baseline, a uniform fixed-weight control, and the proposed adaptive-weight method. The adaptive method was shown to achieve the fastest navigation time along with the most stable and smooth force behavior, with the variability of the avoidance force reduced substantially compared to both baselines without sacrificing path efficiency. Quantitatively, the adaptive method achieved a navigation time of 17.20 seconds, an average avoidance force of 2.848 N, and a force standard deviation of 4.361 N, representing a 22% reduction in travel time and a 74% reduction in force variability compared to the fixed-weight baseline, with a path-following efficiency of 96.6%.
| Item Type: | Thesis (Masters) |
|---|---|
| Uncontrolled Keywords: | Mobile Robot, Adaptive Force Field, Obstacle Avoidance, Beta-Weighted Repulsion, Path Planning, Autonomous Navigation,Mobile Robot, Adaptive Force Field, Obstacle Avoidance, Beta-Weighted Repulsion, Path Planning, Autonomous Navigation |
| Subjects: | T Technology > T Technology (General) T Technology > T Technology (General) > T57.62 Simulation T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK3070 Automatic control |
| Divisions: | Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20101-(S2) Master Thesis |
| Depositing User: | Muhammad `aqil Rayhan Majid |
| Date Deposited: | 01 Aug 2026 05:26 |
| Last Modified: | 01 Aug 2026 05:26 |
| URI: | http://repository.its.ac.id/id/eprint/141283 |
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