76 citations · 164 across the 14 of their papers we have counts for
6 papers · 1 filter
All You Need Is Low Fidelity: Zero-Shot Sim-to-Real of Learned Robotic Fish Control
Liam Maloney, Simon Ramchandani, Mike Y. Michelis +2
Complex tasks for underwater robots remain limited by the capabilities of their controllers. Learning a better one for a soft, underactuated robotic fish trades simulator cost agai…
Orientation Control of Soft Robots via Adiabatic Spectral Submanifolds
Aron Karakai, Roshan S. Kaundinya, Mike Yan Michelis +2
Soft robots are commonly sought for safety-critical interactions in delicate environments, where accurate position and orientation control is imperative. Model predictive control (…
Swim2Real: VLM-Guided System Identification for Sim-to-Real Transfer
Kevin Qiu, Kyle Walker, Mike Y. Michelis +2
We present Swim2Real, a pipeline that calibrates a 16-parameter robotic fish simulator from swimming videos using vision-language model (VLM) feedback, requiring no hand-designed s…
A Unified Low-Dimensional Design Embedding for Joint Optimization of Shape, Material, and Actuation in Soft Robots
Vittorio Candiello, Manuel Mekkattu, Mike Y. Michelis +1
Soft robots achieve functionality through tight coupling among geometry, material composition, and actuation. As a result, effective design optimization requires these three aspect…
Simple Models, Real Swimming: Digital Twins for Tendon-Driven Underwater Robots
Mike Y. Michelis, Nana Obayashi, Josie Hughes +1
Mimicking the graceful motion of swimming animals remains a core challenge in soft robotics due to the complexity of fluid-structure interaction and the difficulty of controlling s…
Learning, Solving and Optimizing PDEs with TensorGalerkin: an efficient high-performance Galerkin assembly algorithm
Shizheng Wen, Mingyuan Chi, Tianwei Yu +5
We present a unified algorithmic framework for the numerical solution, constrained optimization, and physics-informed learning of PDEs with a variational structure. Our framework i…