RACLAB News

Kapsül RACLAB ROVER team achieved the highest score in history on the Autonomous Track at the TEKNOFEST Unmanned Ground Vehicle Competition, securing 1st Place and the Best Design Award. The team ranked 4th in the overall standings.

Kapsül RACLAB UAV Team successfully completed all challenging missions with our autonomous UAV 'ŞAHİ' at the prestigious SUAS 2026 competition held in the USA, ranking 9th worldwide.

Kapsül RACLAB NOVA was awarded the Most Original Design Award at the TEKNOFEST Unmanned Underwater Systems (Blue Homeland) Competition organized by ASELSAN.

"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.

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.

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.

RACLAB members Seher Tiryaki, Ece Erkmen and Hasan Hüseyin Tiryaki won 2nd place at Ideathon Konya, organized by Emlak Konut GYO on "Smart Vertical Transportation & Integrated Construction Robotics".

RACLAB published research on "Deep RL-based 1-DOF helicopter control" in Physica Scripta, an SCI-E indexed journal.

RACLAB published "Maximum weighted traffic flow signal control" in the Turkish Journal of Electrical Engineering and Computer Sciences (TUBITAK EEJ), an SCI-E indexed journal.

RACLAB published research on LQR-PID and LQR-FOPID quadrotor control methods in the International Journal of Applied Mathematics and Computer Science (IJAAC), an SCI-E indexed journal.

RACLAB published "Disturbance-tolerant quadrotor control using a hybrid LQR and super-twisting sliding mode approach" in Scientific Reports (Nature Portfolio) — a top-tier SCI-E indexed journal.

RACLAB published "Advancing Remote Sensing With Few-Shot Learning: A Comprehensive Review of Methods, Challenges, and Future Directions" in Transactions in GIS, an SCI-E indexed journal.

RACLAB researchers Salim AZAK, Fırat BOZKAYA, Şükrücan TIGLIOGLU, Abdullah YUSEFI, and Akif DURDU published "A Unified Monocular Vision-Based Driving Model for Autonomous Vehicles with Multi-Task Capabilities" in IEEE Transactions on Intelligent Vehicles (Vol. 10, Issue 9, September 2025). This work advances end-to-end autonomous driving using deep learning.

Prof. Akif DURDU received the UDHAM (Unmanned Aircraft System Education and Research Platform) "Outstanding Contribution in Leadership" award for his contributions to unmanned systems education and research in Türkiye.

RACLAB FAAL team secured third place in the Digital Technologies in Industry competition at TEKNOFEST 2025 in the advanced category, competing against top university teams across Türkiye.

RACLAB SİGUN achieved second place and won the "Most Original Software" special award in the TEKNOFEST 2025 Robotaxi Passenger Autonomous Vehicle competition, demonstrating innovative AI and sensor fusion solutions.

RACLAB EZEL competed in the TEKNOFEST 2025 Mavi Vatan (Blue Homeland) unmanned surface vehicle competition, gaining valuable experience in autonomous maritime systems.

RACLAB teams participated in the TEKNO-SEL competition organized by Selçuk University, continuing to develop their UAV and autonomous systems capabilities.

RACLAB researchers Cihat Talat AKPINAR, Özcan KOSAR, and Akif DURDU presented two papers at IEEE INFOTEH 2025: "Enhancing the Performance of Machine Learning Classification Models" and "Virtual Reality Solutions for Troubleshooting Autonomous Industrial Mobile Robots".

RACLAB researchers presented 3 papers at the IEEE ISAS 2025 Conference in Gaziantep: Real-Time Safety Helmet & Vest Detection (YOLO), Model Predictive Control for Path Tracking in Autonomous Vehicles, and Comparative Performance Analysis of ROS 2 Local Controllers on AMR. Authors: Mamady Cheick Souare, Ibrahim TOY, Abdullah YUSEFI, Özcan KOSAR, Cihat Talat AKPINAR, Akif DURDU.

RACLAB researchers presented 5 papers at the IEEE ATEE 2025 International Conference in Bucharest: RobustPointNet++ (LiDAR), Autonomous Human Tracking (Vision-LiDAR Fusion + MPC), Self-Recovery Algorithm for AMRs (Yiğit Bora CAGIRAN), Reinforcement Learning-Based Traffic Signal Control (Sinan ILGEN), and VR Solutions for Industrial Mobile Robots. Authors: Abdullah YUSEFI, İbrahim TOY, Cihat Talat AKPINAR, Sinan ILGEN, Akif DURDU.

RACLAB published "Consensus-based Virtual Leader Tracking Swarm Algorithm with GDRRT*-PSO for Path-Planning of Multiple UAVs" in Swarm and Evolutionary Computation, a highly regarded SCI-E indexed journal.

The 25th National Conference on Automatic Control (TOK 2024) was held in Konya. RACLAB contributed 8 research papers covering autonomous driving, quadrotor control, UAV tracking, and traffic signal systems — a record for a single conference.

RACLAB ARES won the "Most Original Design" special award at TEKNOFEST 2023 Agricultural UAV competition. The team's innovative approach to agricultural drone design stood out among competing universities.

RACLAB published research on intelligent traffic signal control using machine learning in IEEE Access, contributing to the K-TASK adaptive traffic control research line.

Two papers published in Neural Computing and Applications covering a new deep learning method for self-driving vehicles using multi-input CNN, and focal loss applications in learning algorithms.

RACLAB presented three papers at IEEE ATEE 2023, including designs for AUV electronic boards, PC communication interfaces for underwater vehicles, and edge detection with deformable CNNs.

RACLAB published a study on 2D and 3D medical image segmentation in Mathematical Biosciences and Engineering (SCI-E).

RACLAB published research on using CNNs for pump status classification in Engineering Science and Technology, an International Journal (SCI-E).

RACLAB published a comprehensive comparison between CNNs and Capsule Networks for classification tasks in Applied Sciences (SCI-E).

RACLAB SİGUN won first place in the TEKNOFEST 2022 Robotaxi Passenger Autonomous Vehicle competition! The team's deep learning-based perception and autonomous navigation system outperformed all competitors. This was RACLAB's first national robotaxi championship.

RACLAB published a comprehensive systematic literature review on Extended Kalman Filter-based SLAM for autonomous navigation in IEEE Access, becoming a key reference in the robotics field.

RACLAB published a novel YOLO approach for recognizing plants with nutrient deficiencies in Scientific Reports (Nature portfolio), expanding RACLAB's AI research into agricultural applications.

RACLAB published research on human action recognition for robotic applications using Bag of Visual Words in the journal Complexity (SCI-E indexed, Wiley), combining machine learning with motion analysis for HRI.

Published in Electronics Letters (IET, SCI-E) — "Position Estimation of a Robot Using Unscented Kalman Filter" — contributing to RACLAB's core research on autonomous navigation and state estimation.

RACLAB published research on using state-of-the-art deep learning algorithms for real-time embedded object detection systems in the International Journal of Advanced Robotic Systems (SCI-E), targeting UAV and ground robot applications.

RACLAB competed in the prestigious AUVSI SUAS (Student Unmanned Aerial Systems) international competition in Maryland, USA, achieving an impressive 11th place out of 67 competing university teams from around the world — a significant improvement from 2018.

RACLAB's UAV team (Aybars, now TULPARS) won first place at TEKNOFEST 2019 International UAV Competition! This was RACLAB's first major national UAV championship, establishing RACLAB as a top autonomous systems lab in Türkiye.

RACLAB published cutting-edge research on deep learning-based 3D object detection for autonomous systems in IEEE Access, laying the groundwork for future autonomous vehicle perception research.

RACLAB's first international competition appearance at the AUVSI SUAS (Student Unmanned Aerial Systems) competition in Maryland, USA. The team finished 20th out of 70 competing university teams in their debut, demonstrating strong capability for a first-time international participant.

The Robotics, Automation and Control Laboratory (RACLAB) was established at what was then Selçuk University (now Konya Technical University) by Prof. Akif DURDU. RACLAB started with autonomous UAV research and TÜBİTAK 2209-A student projects, quickly growing into a comprehensive robotics research center.

RACLAB's early publication "Modified Control of PMSM using Backstepping Design" appeared in Elektronika ir Elektrotechnika (SCI-E indexed), demonstrating the lab's foundational work in control systems before expanding into robotics.