Perancangan Sistem Kontrol MPC Non-Linier pada Mobil Otonom Berbasis Robot Operating System untuk Menghindari Obstacle Dinamis

Putra, Ghazi Amalul (2025) Perancangan Sistem Kontrol MPC Non-Linier pada Mobil Otonom Berbasis Robot Operating System untuk Menghindari Obstacle Dinamis. Other thesis, Institut Teknologi Sepuluh Nopember.

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Abstract

Penelitian ini bertujuan untuk merancang sistem kontrol Nonlinear Model Predictive Control (NMPC) pada kendaraan otonom berbasis ROS2 yang mampu menghindari obstacle dinamis dan merespons kondisi lalu lintas secara adaptif. Sistem dirancang menggunakan model kinematik sepeda dalam bentuk diskret sebagai prediktor, dan diuji dalam simulator CARLA melalui empat skenario realistis: pelacakan lintasan lurus, tikungan, lampu lalu lintas, dan obstacle avoidance. Sistem kontrol mempertimbangkan berbagai constraint fisik dan lingkungan seperti batas sudut kemudi, kecepatan, serta jarak terhadap obstacle dan garis henti. Validasi dilakukan melalui analisis error pelacakan menggunakan metrik Root Mean Square Error (RMSE) posisi dalam satuan persen terhadap panjang lintasan. Hasil simulasi menunjukkan bahwa sistem mampu menyelesaikan semua skenario dengan nilai RMSE posisi relatif yang rendah, yakni berkisar antara ±0.08% hingga ±4.84%, tergantung pada kompleksitas lingkungan. Nilai RMSE yang kecil ini menunjukkan bahwa kontroler NMPC mampu mengarahkan kendaraan dengan akurat dan stabil. Bahkan dalam skenario yang kompleks, deviasi posisi terhadap jalur referensi justru merupakan bentuk adaptasi sistem terhadap constraint keselamatan, bukan kegagalan pelacakan. Secara keseluruhan, sistem NMPC yang dirancang berhasil menunjukkan performa pelacakan yang presisi, kontrol kecepatan yang adaptif, serta manuver penghindaran yang responsif. Integrasi dengan ROS2 dan simulator Carla juga memungkinkan pengujian sistem secara end-to-end dalam kondisi yang menyerupai dunia nyata.

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This research aims to design a Nonlinear Model Predictive Control (NMPC) system for autonomous vehicles based on ROS2, capable of avoiding dynamic obstacles and responding adaptively to traffic conditions. The control system is developed using a discretized kinematic bicycle model as the prediction model and tested in the CARLA simulator through four realistic scenarios: straight-line tracking, cornering, traffic light navigation, and obstacle avoidance. The controller incorporates physical and environmental constraints such as steering angle limits, velocity bounds, and safe distances from obstacles and stop lines. Validation is conducted using Root Mean Square Error (RMSE) of positional tracking, expressed as a percentage relative to the total path length. Simulation results show that the system successfully completes all scenarios with low RMSE values, ranging from ±0.08% to ±4.84%, depending on the scenario complexity. These values indicate that the NMPC controller is capable of guiding the vehicle with high accuracy and stability. In more complex situations, the deviation from the reference path reflects the system's intelligent adaptation to safety constraints rather than a failure in tracking accuracy. Overall, the designed NMPC system demonstrates precise trajectory tracking, adaptive velocity control, and responsive obstacle avoidance. Its integration with ROS2 and the Carla simulator enables comprehensive end-to-end testing under conditions closely resembling real-world environments.

Item Type:	Thesis (Other)
Uncontrolled Keywords:	Mobil otonom, Nonlinear Model Predictive Control, obstacle dinamis, ROS2, Simulator Carla
Subjects:	T Technology > T Technology (General) > T57.8 Nonlinear programming. Support vector machine. Wavelets. Hidden Markov models. T Technology > TC Hydraulic engineering. Ocean engineering T Technology > TG Bridge engineering T Technology > TJ Mechanical engineering and machinery > TJ213 Automatic control. T Technology > TJ Mechanical engineering and machinery > TJ217.2 Robust control T Technology > TL Motor vehicles. Aeronautics. Astronautics > TL152.8 Vehicles, Remotely piloted. Autonomous vehicles.
Divisions:	Faculty of Industrial Technology > Physics Engineering > 30201-(S1) Undergraduate Thesis
Depositing User:	Ghazi Amalul Putra
Date Deposited:	04 Aug 2025 08:39
Last Modified:	04 Aug 2025 08:39
URI:	http://repository.its.ac.id/id/eprint/124456

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