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2025 Projeler

Format: On Campus
Number of Students: 1
Duration of Project: 21 July – 8 August
Project Supervisor: Associate Professor Barkan Uğurlu
Research Areas: Developing a lightweight and explainable AI library for robotics applications
Application Deadline: 4 July 2025

Project Description:

The internship focuses on developing a lightweight and explainable AI library for robotics applications. Interns will design and implement a neural network model to control a maze-solving mini-robot equipped with wheel encoders, bump sensors, and an infrared sensor. The project aims to foster hands-on experience in AI-based robotics, encouraging creativity and problem-solving skills.

About the Project:

The mini-robot is a compact and versatile platform designed for educational and experimental purposes. With its onboard sensors and actuators, the robot can interact with its environment, navigate through mazes, and respond to obstacles. Interns will work on both software and hardware aspects, gaining insights into robotics, machine learning, and embedded systems.

Project Objectives:

Develop a lightweight and explainable neural network model for maze-solving tasks.
Integrate the AI model with the robot’s hardware for real-time decision-making.
Enhance understanding of sensor fusion and robotics control systems.
Inspire students to tackle more advanced challenges in robotics and AI.

Project Tasks

Research Phase:

Review basic principles of neural networks and robotics.
Study existing algorithms for maze solving.

Development Phase:

Implement a neural network model suitable for the mini-robot.
Train and validate the model using simulation or small-scale environments.
Optimize the model for real-time performance and explainability.

Integration Phase:

Program the robot’s microcontroller (Arduino) to interface with the sensors and AI model.
Test and debug the robot’s behavior in a controlled maze environment.

Documentation Phase:

Document the AI library’s design, implementation, and testing process.
Prepare a presentation or report summarizing the project outcomes.

Deliverables:

A lightweight, explainable AI library for maze-solving robots.
A functional prototype of the mini-robot demonstrating maze-solving capabilities.
Comprehensive documentation, including source code, usage instructions, and a project report.
A final presentation showcasing the project’s progress and outcomes.

Benefits for the Student:

Hands-on experience in AI and robotics.
Knowledge of neural networks, sensor integration, and Arduino programming.
Development of problem-solving, teamwork, and project management skills.
Opportunity to contribute to a practical and inspiring robotics project.
Exposure to a research-oriented environment, paving the way for advanced studies or careers in robotics and AI.

Requirements:

Basic understanding of calculus and linear algebra.
Proficiency in Arduino programming and familiarity with embedded systems.
Interest in robotics, artificial intelligence, and machine learning.
Ability to work independently and as part of a team.
Commitment to completing the project within the specified timeframe.

This internship offers a unique opportunity for aspiring young engineers to gain hands-on experience in the rapidly evolving field of AI-based robotics. We are looking for motivated and curious individuals ready to challenge themselves and contribute to innovative solutions.

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2025 Projeler