Konya Technical University · Est. 2014

Pioneering Autonomous
Systems Research

RACLAB is an interdisciplinary R&D laboratory at Konya Technical University, pushing the boundaries of robotics, automation, and intelligent control through cutting-edge research in UAVs, autonomous ground & underwater vehicles, and smart transportation.

Explore Research Learn About Us

RACLAB — Robotics Automation Control Laboratory

R Robotics A Automation C Control LAB oratory

2014 Founded

About RACLAB

Robotics, Automation & Control
Laboratory

Founded in 2014 under the leadership of Prof. Dr. Akif DURDU, RACLAB is a project-based R&D laboratory at Konya Technical University where undergraduate and graduate students work alongside academics on real-world engineering challenges.

Our philosophy: students learn not only technical skills but also teamwork, communication, and product-development thinking through real problem scenarios.

🚁

UAV Systems Fixed & rotary wing drones

🚗

Autonomous Vehicles Ground & underwater robots

🧠

AI & Deep Learning Perception & decision-making

🏭

Industry Collaboration TÜBİTAK, KOSGEB, EU projects

Full Story Get in Touch

Student Research Projects

Journal Articles

Awards & Championships

Funded Research Projects

Research Areas

What We Work On

RACLAB conducts advanced R&D across six core domains, integrating perception, planning, control, and communication into deployable autonomous systems.

Unmanned Aerial Vehicles (UAV)

Design and development of fixed-wing & rotary-wing UAV platforms. Autonomous flight, GPS-denied navigation, real-time image processing, swarm coordination, and indigenous flight control software.

SLAM Vision Swarm Deep Learning

Learn More

Autonomous ground vehicle in urban environment

Autonomous Ground Vehicles (UGV)

Sensor-fusion-based localization, lane detection, obstacle avoidance, path planning and autonomous control for self-driving car platforms and industrial AGVs.

LiDAR ROS SLAM AI Control

Learn More

Autonomous Underwater Vehicles (AUV)

GNSS-independent navigation using IMU–DVL–camera–depth sensor fusion, obstacle detection/avoidance, and autonomous mission planning for underwater environments.

DVL IMU Fusion Sonar

Learn More

Smart Transportation Systems

IoT-based adaptive traffic signal control, V2I communication modules, digital twin technology for intersections, and AI-driven macroscopic traffic analysis software.

IoT V2I Digital Twin

Learn More

Human-Robot Interaction

Estimating and reshaping human intention in collaborative HRI scenarios using HMM and OOM methods. Gesture recognition, action understanding, and safe motion planning.

HMM OOM Gesture

Learn More

Sensor Fusion & SLAM

Multi-sensor integration (IMU, LiDAR, camera, GPS) for robust state estimation, simultaneous localization and mapping, and multi-agent situational awareness.

LiDAR IMU EKF Visual SLAM

Learn More

View All Research Areas

Featured Projects

Our Active & Recent Projects

From national championships to EU-funded international research, our teams deliver real-world impact.

Active 2021–Present

RACLAB SİGUN — Autonomous Robotaxi

AI-powered self-driving vehicle competing in TEKNOFEST Robotaxi championships. 2× "Best Original Software" award & 2× Runner-Up (2022, 2025).

Project Details

Champion 2021–2025

RACLAB NOVA — Underwater AUV

Autonomous underwater vehicle with vision-based mission execution. TEKNOFEST 2025 Underwater Systems Champion & Best Team Spirit award.

Project Details

Champion 2017–Present

RACLAB İHA — Autonomous Drone

Multi-year TÜBİTAK UAV competition entry. 2019 National Champion · 2017 Runner-Up · Multiple Performance Awards (2023, 2025).

Project Details

Industry 2021–2025

Autonomous Outdoor Shuttle — MPG

Sensor-fusion-based autonomous shuttle for outdoor patrol/service missions. Developed in collaboration with MPG Machinery Production Group.

Project Details

TÜBİTAK 1511 2018–2020

K-TASK — Coordinated Adaptive Signal Control

Fully adaptive, coordinated traffic signal control system for urban intersections. Developed with Innomotive under TÜBİTAK 1511 priority R&D programme.

Project Details

Active · EU Funded 2022–Present

Smart Sugarbeet Monitoring — ERA-NET

Satellite-controlled incentive system for sustainable sugarbeet production. International ERA-NET Cofund ICT-AGRI-FOOD project with Agrovisio.

Project Details

View All Projects →

Achievements

Competition Excellence

Since 2016, RACLAB teams have competed nationally and internationally, winning championships and recognition across 15+ competition platforms.

🏆

TEKNOFEST 2025 — Underwater Systems Champion RACLAB NOVA · Best Team Spirit Award · Istanbul, 2025

🥇

TÜBİTAK UAV Championship 2019 RACLAB Aybars · Rotary Wing Category National Champion

🥇

OpenZeka MARC 2019 — University Champion Mini Autonomous Car — highest score among all universities

🥈

TEKNOFEST 2025 — Robotaxi Runner-Up RACLAB SİGUN · "Best Original Software" Award (3rd time)

🌍

AUVSI SUAS 2019 — 11th Place / 67 Teams (USA) International UAV Systems Student Competition, Maryland

🏆

ODTÜ Robot Days — Multiple Champions (2020) RACLAB Tugberk · Autonomous UAV-Image Processing category

🚁

TEKNOFEST UAV Awards

🚗

Robotaxi Awards

🌊

Underwater Awards

🌍

International Awards

Full Awards List →

Our Team

The People Behind RACLAB

A multidisciplinary team of researchers, graduate students, and undergraduate engineers from Computer, EE, Mechanical, and Industrial Engineering.

Prof. Dr. Akif DURDU

Lab Director & Principal Investigator

Electrical & Electronics Engineering

🌐 Website 💼 LinkedIn

Graduate Researchers

Zülal Hilal Yildiz BUDAK

PhD Researcher

Decision Support Systems

Gökberk AY

PhD Researcher

AI | Smart Agriculture

İbrahim TOY

PhD Researcher

ADAS | Intelligent Control

Cihat Talat AKPINAR

MSc Researcher

Autonomous Systems

Ahmet ŞAHİN

MSc Researcher

Intelligent Transportation

Meet the Full Team →

Publications

Research Output

A comprehensive collection of journal articles, conference papers, book chapters, theses, and other academic outputs from RACLAB researchers.

42+

SCI-E Journal Articles

Total Journal Articles

60+

Conference Papers

Book Chapters

MSc/PhD Theses

23+

Funded R&D Projects

Latest Publications

Deep Reinforcement Learning-Based Control of a 1-DOF Helicopter: A Comparative Analysis

Serkan BUDAK, Cemil SUNGUR, Akif DURDU

Physica Scripta, Volume 101, Issue 2, Jan. 2026

SCI-E Journal 2026

A Unified Monocular Vision-Based Driving Model for Autonomous Vehicles with Multi-Task Capabilities

Salim Azak, Fırat Bozkaya, Şükrücan Tığlıoğlu, Abdullah Yusefi, Akif DURDU

IEEE Transactions on Intelligent Vehicles, Vol. 10, Issue 9, Sep. 2025

SCI-E · WOS Q1 Journal 2025

LiDAR-Camera Fusion Based 3D Object Detection with Tracking Using Extended Kalman Filter

Şükrücan Tığlıoğlu, Fırat Bozkaya, Akif DURDU

TEKNOFEST 2025 / IEEE Conference, 2025

Conference 2025

Consensus-based Virtual Leader Tracking Swarm Algorithm with GDRRT*-PSO for Path-Planning of Multiple UAVs

Berat YILDIZ, Muhammet Fatih Aslan, Akif DURDU, Ahmet Kayabaşı

Swarm and Evolutionary Computation, Vol. 88, Article 101612, 2024

SCI-E Journal 2024

View All Publications

From the Lab

Stay up to date with RACLAB's latest competitions, research milestones, and announcements.

Project 2026 · TÜBİTAK 1001

🚀 TÜBİTAK 1001 Project: Autonomous Navigation Software Kit

"Development of an Autonomous Navigation Software Kit Based on Multi-Sensor Fusion and Deep Learning-Aided Factor Graph Optimization in GNSS-Denied Underwater Environments" — Principal Investigator: Prof. Dr. Akif DURDU.

Publication 2026 · Actuators

📰 Paper in Actuators (SCI-E)

RACLAB published "Hybrid LQR-SMC/STSMC with BB-BC Optimization for Enhanced Transient Performance and Chattering Suppression in a 3-DOF Hover System" in Actuators, an SCI-E indexed journal.

Competition July 2026 · RoboSub · Irvine, California

🤿 RACLAB NOVA at RoboSub 2026 — Irvine, California

RACLAB NOVA participated in the 29th International RoboSub Autonomous Underwater Systems Competition in Irvine, California (July 11–16, 2026) with teams from 9 countries. Among 58 finalists, our team reached the semifinals, competing against top-100 universities worldwide with limited resources.