Electrical and Electronics Engineer with experience across robotics systems and engineering projects. Currently starting a MSc in Systems and Control at TU Delft.
I work at the intersection of robotics, control,and software develepoment with hands-on experience in ROS1, C++, Python, and simulation-based development. My interests include autonomous systems, robot control, and engineering-driven robotics solutions.
- 💼 LinkedIn: https://www.linkedin.com/in/panagiotisioakeimidis/
- 💻 GitHub: https://github.com/p-ioakeimidis
This project demonstrates state estimation for a differential two-wheel (differential drive) mobile robot using the Extended Kalman Filter (EKF) in ROS1 Noetic. The robot is simulated in Gazebo and visualized in RViz, with separate configurations for local and global localization.
This project implements a complete autonomous navigation system for a differential drive mobile robot using ROS1 Noetic. It extends a previously developed EKF-based localization system and adds global and local path planning capabilities using the ROS Navigation Stack.
A Python and OpenCV-based lane following system that detects road lane markings from an MP4 video, estimates the steering angle in real time, and outputs a normalized steering command using classical computer vision techniques.
This project implements a Tiny Machine Learning (TinyML) model for controlling a two-wheeled self-balancing robot using the Arduino Nano 33 BLE Sense. A MATLAB/Simulink model with an LQR-based Full-State Feedback controller was used to generate training data, which was then used to train a lightweight model in Edge Impulse. The final model was deployed using TensorFlow Lite Micro for real-time embedded control.
A real-time object detection system using YOLO and OpenVINO to detect traffic signs, lights, pedestrians, and vehicles from video input with optimized inference performance.
- Autonomous robotics
- Motion planning
- Decisiong making
- State estimation
- Sensor fusion