Denis Cehajic

Papers

Total Citations

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About

Denis Cehajic’s research lies at the intersection of physical human-robot interaction, humanoid motion imitation, and sensor-based manipulation. His work focuses on enabling robots to work safely and intuitively alongside people, particularly in tasks requiring physical cooperation. Cehajic’s most cited paper (31 citations) addresses a fundamental challenge in human-robot manipulation: accurately estimating unknown object dynamics to avoid disturbing the human partner with miscalculated forces. He further advanced this area by using wearable motion sensors to estimate human grasp poses, reducing interaction wrenches that can disrupt collaboration and intention recognition. In humanoid robotics, Cehajic developed a method for online human-to-humanoid motion imitation that handles support changes—such as stepping or foot placement—using inverse kinematics with task specification (24 citations). This work is notable for enabling more natural locomotion in humanoid robots. With a total of over 68 citations across his key publications, Cehajic’s contributions are essential for creating robots that can physically cooperate with humans in dynamic, real-world environments, from manufacturing to assistive care.