MATLAB sample codes for mobile robot navigation

This repository contains the Matlab code for the lateral and longitudinal control of vehicle modeled based on the Bicycle-Model. This work was carried out by me and my colleague Suleyman as part of the smart transportation course.

Control system design for platoon of autonomous vehicles

Dataset and Evaluation Scripts for Obstacle Detection via Semantic Segmentation in a Marine Environment

The code for the project Distributed Nonlinear Model Predictive Control (DNMPC) for vehicle platooning

Domain Adaptation for Semantic Segmentation at Nighttime

My work during the research project "Comfort-oriented adaptive cruise control of an autonomous vehicle" at GIPSA-lab, Jan.-Jun. 2020, later extended into LPV control of a semi-active suspension system

We propose a driver modeling process of an intelligent autonomous driving policy, which is obtained through Q-learning.

This GitHub repository implements two Model Predictive Control (MPC) approaches for active front steering systems in autonomous vehicles. The methods are inspired by groundbreaking scientific papers. The project utilizes MATLAB and Simulink, requiring

This is a repository of the Open Aided Navigation project. The project aims to demonstrate and explain state of the art methods of modern aided inertial and satellite (GNSS) navigation, and multi-sensor localization. The software provided in this repository is written in Matlab.

DRIVE: A Digital Network Oracle for Cooperative Intelligent Transportation Systems

Configuring the radar FMCW waveform based on the system requirements and simulating the radar signal propagation and moving target scenario. Finally, post processing the radar signal using 1st FFT, 2nd FFT, and CA-CFAR to estimate the target's range and velocity.

Probabilistic framework for behavior prediction in autonomous vehicles

Modeling, Planning and Nonlinear Control Techniques For Autonomous Vehicles 🎛️🚘

MATLAB sample codes for Robotics engineering

Tool to design and optimize autonomous vehicle concepts.

Autonomous Racing using a Hybrid Imitation-Reinforcement Learning Architecture

Multi-Camera surveillance systems are being increasingly used to enhance safety and security and the possibility to mount cameras on Unmanned Aerial Vehicles (UAVs) extends their capabilities to a whole new level. The aim of this project is to find a possible solution to the Interactive Surveillance problem using multiple UAV mounted cameras.

The goal of this project is to use MATLAB to implement a Radar target generation and detection system.

This project uses Recurrent Neural Networks (RNNs) to classify the behavior of objects in traffic based on their risk level, enhancing the safety of autonomous vehicles. Developed as part of the MATLAB-Simulink Challenge by MathWorks.