Artem Beger
Papers
1
Total Citations
17
H-Index
1
About
Artem Beger is a pioneering researcher in soft robotics, specializing in proprioceptive sensing and shape estimation for highly constrained robotic systems. His work addresses a critical challenge: enabling soft robots to accurately perceive their own shape and applied forces using only internally embedded sensors, without relying on bulky external tracking or constant-curvature assumptions. Beger’s most-cited paper, “Multi-Tap Resistive Sensing and FEM Modeling Enables Shape and Force Estimation in Soft Robots” (2023, 17 citations), introduces a novel approach that combines multi-tap resistive sensing with finite element modeling to achieve precise, real-time shape and force reconstruction. This work has significant implications for soft robots operating in tight packaging environments, such as surgical tools or search-and-rescue devices, where traditional sensing methods fail. By moving beyond simplistic models, Beger’s contributions advance the field toward more robust, practical soft robotic systems. His research is widely recognized for bridging simulation and hardware, offering a scalable solution for embedded proprioception. With growing citation impact, Beger is establishing himself as a key innovator in soft robot sensing and control.
Research Focus
Key Achievements
Top Papers
- 1