Omer Shapira
Papers
2
Total Citations
11
H-Index
2
About
Omer Shapira’s research lies at the intersection of human-robot interaction, teleoperation, and soft robotics for virtual reality. His most impactful work, “Assistive Tele-op: Leveraging Transformers to Collect Robotic Task Demonstrations” (2021, 8 citations), introduces a novel framework that shares autonomy between human operators and robots. By using transformer-based models, Shapira enables more intuitive communication of intent and future reasoning, significantly streamlining the collection of robotic task demonstrations to improve learned models. This contribution addresses a critical bottleneck in robotics: bridging the disparate ways humans and robots reason about tasks. In earlier work, “Stretchable transducers for kinesthetic interactions in virtual reality” (2017, 3 citations), Shapira explored soft robotics to create immersive haptic feedback. He demonstrated fluidic elastomer actuators (FEAs) that deliver force feedback through a motion-tracked controller, enabling safe, kinesthetic experiences in augmented and virtual reality. This work highlights his ability to merge cutting-edge materials science with practical VR applications. Shapira’s research is notable for its focus on making robotic data collection more efficient and VR interactions more tactile, with potential impacts on training, simulation, and assistive technologies.
Research Focus
Key Achievements
Top Papers
- 1
- 2Stretchable transducers for kinesthetic interactions in virtual reality3 citations · 2017