At AUTRIS, I developed a mobile robot’s autonomous navigation solution using deep reinforcement learning with DQN and Double DQN. I simulated and evaluated the algorithms in ROS 2 and Gazebo, then deployed and validated them on a real robot.
I also diagnosed and corrected hardware issues on the existing robot, and integrated YDLIDAR X4 data for obstacle detection and navigation. My projects include embedded systems, robot control, and testing and validation, using tools such as C/C++, Python, STM32, and LabVIEW.

