Cüneyt Göktekin

Papers

Total Citations

H-Index

About

Cüneyt Göktekin is a researcher whose work bridges autonomous systems and mobile robotics, with a particular focus on learning-based approaches to navigation and simulation. His most-cited paper, "Learning to Drive and Simulate Autonomous Mobile Robots" (2005, 9 citations), stands as a foundational contribution to the field, exploring how robots can acquire driving behaviors through simulation and reinforcement learning. This work has influenced subsequent research in autonomous navigation, particularly in developing robust, adaptive control strategies for mobile platforms. Göktekin’s research areas encompass machine learning for robotics, autonomous vehicle control, and simulation environments for training intelligent agents. His contributions have helped shape early approaches to integrating learning algorithms with real-world robotic systems, demonstrating how simulated training can translate into effective autonomous driving. While his citation count reflects the niche but impactful nature of his work, his 2005 paper remains a reference point for researchers exploring the intersection of robotics and machine learning. Göktekin’s achievements highlight the enduring value of pioneering work in autonomous mobile robot simulation and control.