Papers
5
Total Citations
55
H-Index
4
About
Ozan Kaya is a roboticist whose research bridges the critical gap between safe human-robot interaction and intelligent automation. His work centers on three key areas: compliant actuation, human action prediction, and autonomous trajectory planning. Kaya’s most significant contribution is a novel method for estimating external force and torque using only position sensors in antagonistic variable stiffness actuators (VSAs)—a breakthrough that eliminates the need for expensive, fragile force sensors, enabling safer, more intuitive physical human-robot collaboration (22 citations). He has also advanced the field of cognitive robotics by demonstrating that humans predict actions using grammar-like structures, a finding that informs more fluent human-robot teamwork (11 citations). In manufacturing, Kaya has developed and compared state-of-the-art path planning algorithms, including a PSO-optimized RRT-APF hybrid for collision-free robotic welding (9 citations), and designed a series elastic gripper capable of object detection and recognition through touch alone (9 citations). His recent work on industrial camera-aided trajectory planning for reflective surfaces further showcases his commitment to solving real-world automation challenges. With a growing citation record and a focus on both fundamental theory and practical application, Kaya is establishing himself as a versatile researcher shaping the future of safe, perceptive, and autonomous robotic systems.
Research Focus
Key Achievements
Top Papers
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- 2Humans Predict Action using Grammar-like Structures11 citations · 2020
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