Fuzzy Predictive Control Untuk Path Tracking Dan Obstacle Avoidance Pada Autonomous Mobile Robot

Islamiati, Fitri Nur (2026) Fuzzy Predictive Control Untuk Path Tracking Dan Obstacle Avoidance Pada Autonomous Mobile Robot. Other thesis, Institut Teknologi Sepuluh Nopember.

Text 5022221068-Undergraduate_Thesis.pdf - Accepted Version Restricted to Repository staff only Download (4MB) | Request a copy

Abstract

Perkembangan industri e-commerce mendorong meningkatnya kebutuhan akan sistem otomatisasi transportasi di lingkungan warehouse. Autonomous Mobile Robot (AMR) berperan sebagai sistem transportasi otonom yang bertugas memindahkan barang secara efisien sehingga memerlukan kemampuan path planning, path tracking, dan obstacle avoidance yang andal. Penelitian ini mengusulkan metode Fuzzy Predictive Control (FPC) untuk meningkatkan performa navigasi AMR pada lingkungan warehouse yang dinamis. Perencanaan jalur global dilakukan menggunakan algoritma A* yang dimodifikasi melalui metode neighborhood expansion dan turn penalty, kemudian lintasan dihaluskan menggunakan path smoothing. Sistem path tracking dirancang menggunakan Model Predictive Control (MPC) yang dipadukan dengan Fuzzy Takagi-Sugeno (Fuzzy T-S) sebagai model prediksi, serta logika fuzzy adaptif untuk menyesuaikan matriks pembobot Q dan R berdasarkan kondisi tracking error. Untuk meningkatkan aspek keselamatan, digunakan pengendali Fuzzy Obstacle Avoidance yang diaktifkan ketika robot mendeteksi rintangan dinamis. Hasil pengujian menunjukkan bahwa algoritma A* modifikasi mampu mengurangi jumlah belokan lintasan dari 22 menjadi 5 belokan (77,27%) serta menurunkan waktu komputasi dari 0,8611 s menjadi 0,4356 s (49,4%). Pada pengujian path tracking, FPC menghasilkan performa yang relatif setara dengan MPC konvensional berdasarkan nilai mean error, maximum error, dan RMSE, serta menghasilkan nilai cost function yang lebih rendah melalui penyesuaian matriks pembobot secara adaptif. Selain itu, FPC mampu mengembalikan AMR ke lintasan referensi dalam waktu 1,10 s setelah mengalami gangguan eksternal. Sistem Fuzzy Obstacle Avoidance juga berhasil menghindari rintangan dinamis tanpa terjadi tabrakan dengan jarak minimum robot terhadap rintangan sebesar 0,0170 m. Hasil penelitian menunjukkan bahwa metode yang diusulkan mampu menghasilkan lintasan yang lebih efisien, mempertahankan performa path tracking pada berbagai kondisi pengujian, serta mendukung navigasi AMR secara aman di lingkungan warehouse yang dinamis.
======================================================================================================================================
The rapid growth of the e-commerce industry has increased the demand for automated transportation systems in warehouse environments. Autonomous Mobile Robots (AMRs) play an important role as autonomous transportation systems that efficiently transport goods, requiring reliable path planning, path tracking, and obstacle avoidance capabilities. This study proposes a Fuzzy Predictive Control (FPC) method to improve the navigation performance of AMRs in dynamic warehouse environments. Global path planning is performed using a modified A* algorithm incorporating neighborhood expansion and turn penalty methods, followed by a path smoothing process to generate a smoother trajectory. The path tracking system is designed using Model Predictive Control (MPC) combined with a Fuzzy Takagi-Sugeno (Fuzzy T-S) model as the prediction model, while an adaptive fuzzy mechanism is employed to adjust the Q and R weighting matrices based on the tracking error. To enhance navigation safety, a Fuzzy Obstacle Avoidance controller is activated whenever the robot detects dynamic obstacles. The experimental results show that the modified A* algorithm reduces the number of turns from 22 to 5 (77.27%) and decreases the computation time from 0.8611 s to 0.4356 s (49.4%). In the path tracking evaluation, the proposed FPC demonstrates performance comparable to conventional MPC in terms of mean error, maximum error, and RMSE, while producing a lower cost function through adaptive adjustment of the weighting matrices. Furthermore, the FPC successfully returns the AMR to the reference path within 1.10 s after experiencing an external disturbance. The Fuzzy Obstacle Avoidance system also avoids dynamic obstacles without collisions, maintaining a minimum distance of 0.0170 m from the obstacles. Overall, the proposed method can generate a more efficient path, maintaining path tracking performance under various operating conditions, and supporting safe navigation of AMRs in dynamic warehouse environments.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Autonomous Mobile Robot, Path Tracking, Obstacle Avoidance, Model Predictive Control, Fuzzy Logic
Subjects:	T Technology > TJ Mechanical engineering and machinery > TJ211 Robotics. T Technology > TJ Mechanical engineering and machinery > TJ211.415 Mobile robots T Technology > TJ Mechanical engineering and machinery > TJ217.6 Predictive Control
Divisions:	Faculty of Intelligent Electrical and Informatics Technology (ELECTICS) > Electrical Engineering > 20201-(S1) Undergraduate Thesis
Depositing User:	Fitri Nur Islamiati
Date Deposited:	24 Jul 2026 08:17
Last Modified:	24 Jul 2026 08:17
URI:	http://repository.its.ac.id/id/eprint/137301

Actions (login required)

View Item