Research
Jul 2, 2026·
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1 min read
Ömer Kurkutlu
My research focuses on developing intelligent autonomous robotic systems capable of operating safely and efficiently in complex real-world environments. I am particularly interested in perception-driven autonomy for resource-constrained robots, combining computer vision, deep reinforcement learning, and embedded AI.
My current research directions include:
- Vision-Based Autonomous Navigation using monocular cameras
- Tiny Drone Autonomy for indoor and GPS-denied environments
- Vision-Language-Action (VLA) Models for robotic navigation
- Deep Reinforcement Learning for obstacle avoidance and motion planning
- TinyML and Edge AI for battery-powered and batteryless devices
- Simulation-to-Real Transfer using ROS, Gazebo, Isaac Sim, and Webots
My long-term goal is to develop intelligent robotic systems that can perceive, reason, and navigate autonomously while operating under strict computational and energy constraints.
Authors
PhD Candidate in Electrical and Computer Engineering
I am a Ph.D. candidate in Electrical and Computer Engineering at the University of Illinois Chicago, advised by Dr. Arman Roohi. I specialize in robot learning, Physical AI, and autonomous systems. My research focuses on deep reinforcement learning, vision-language-action models, vision-based navigation, sim-to-real, and resource-constrained robotics, with hands-on experience in NVIDIA Isaac Sim/Isaac Lab, ROS/ROS2, and embedded AI.