Papers
10
Total Citations
209
H-Index
5
About
David Puljiz is a robotics researcher whose work sits at the intersection of human-robot interaction (HRI), augmented reality (AR), and autonomous systems. His most influential contribution, "Human Intention Estimation based on Hidden Markov Model Motion Validation for Safe Flexible Robotized Warehouses" (2018, 106 citations), established him as a leading voice in making robotic workplaces safer by enabling robots to anticipate and respond to human movement intelligently. This foundational work reflects his broader commitment to bridging the gap between human workers and increasingly autonomous industrial environments. Puljiz has made significant strides in AR-assisted robotics, exploring how head-mounted displays like the Microsoft HoloLens can streamline robot cell setup, hand guidance, and teleoperation — reducing the need for expert intervention and making robotics more accessible. His widely cited collection of metaphors for HRI (2021, 49 citations) demonstrates a thoughtful, humanistic dimension to his research, challenging the field to reconsider idealized assumptions about robotic capability and cultivate more realistic human-robot relationships. With contributions spanning VR-based teleoperation, warehouse automation, and robotics education, Puljiz represents a versatile researcher dedicated to making collaborative robotics both safer and more intuitive for everyday users.
Research Focus
Key Achievements
Top Papers
- 1
- 2Collection of Metaphors for Human-Robot Interaction49 citations · 2021
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- 5Stochastic search strategies in 2D using agents with limited perception5 citations · 2012
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- 7Referencing between a Head-Mounted Device and Robotic Manipulators3 citations · 2019
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- 9General Hand Guidance Framework using Microsoft HoloLens2 citations · 2019
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