Ryan Schindeler
Papers
2
Total Citations
45
H-Index
2
About
Ryan Schindeler is a researcher whose work centers on the real-time identification of nonlinear environment dynamics for robotic and haptic systems. His key contributions lie in advancing the practical application of the Hunt-Crossley (HC) model, a physically consistent model for soft object deformation, which is crucial for applications like telerobotics and surgical simulation. Schindeler’s most cited work, "Online Identification of Environment Hunt–Crossley Models Using Polynomial Linearization" (2018, 37 citations), introduces a method for online estimation of environment dynamics, enabling robots to adapt to changing conditions in real time. His earlier paper, "Polynomial linearization for real-time identification of environment Hunt-Crossley models" (2016, 8 citations), laid the groundwork by demonstrating a novel approach to real-time HC model identification, outperforming traditional Kelvin-Voigt models in accuracy. Together, these contributions have significantly improved the ability of robotic systems to interact safely and precisely with deformable environments, with direct implications for medical robotics and haptic feedback. Schindeler’s work is notable for bridging theoretical modeling with practical, real-time implementation, making him a key figure in the field of environment identification for robotic control.
Research Focus
Key Achievements
Top Papers
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