Soft Robotics Lab Project Pages

A list of SRL project websites.

Our Projects with Websites

  1. Simple Models, Real Swimming: Digital Twins for Tendon-Driven Underwater Robots

    Preprint (arXiv), 2026

    Mike Yan Michelis, Nana Obayashi, et al.

    Digital twins for tendon-driven underwater robots, validating simple models with real-world swimming behavior.

  2. Sample-Efficient Real-World Dexterous Policy Fine-Tuning via Action-Chunked Critics and Normalizing Flows

    Preprint (arXiv), 2026

    Chenyu Yang*, Denis Tarasov*, et al.

    Sample-efficient real-world dexterous policy fine-tuning with action-chunked critics and normalizing flows.

    *Equal contribution

  3. SORS: A Modular, High-Fidelity Simulator for Soft Robots

    IEEE RoboSoft, 2026

    Manuel Mekkattu*, Mike Yan Michelis*, et al.

    A modular, high-fidelity simulation framework for soft robots focused on contact-rich manipulation and sim-to-real transfer.

    *Equal contribution

  4. VQ-ACE: Efficient Policy Search for Dexterous Robotic Manipulation via Action Chunking Embedding

    Preprint (arXiv), 2024

    Chenyu Yang*, Davide Liconti*, et al.

    Vector-quantized action chunk embeddings for efficient policy search in dexterous manipulation with MPC and reinforcement learning.

    *Equal contribution

  5. Sensorized Soft Skin for Dexterous Robotic Hands

    IEEE ICRA, 2024

    Jana Egli, Benedek Forrai, et al.

    Sensorized soft skin for high-resolution tactile perception in soft robotics.

  6. Sim-to-Real of Soft Robots with Learned Residual Physics

    IEEE RA-L, 2024

    Junpeng Gao*, Mike Yan Michelis*, et al.

    Hybrid sim-to-real modeling for soft robots that augments analytical simulation with learned residual physics.

    *Equal contribution

  7. Getting the Ball Rolling: Learning a Dexterous Policy for a Biomimetic Tendon-Driven Hand with Rolling Contact Joints

    IEEE-RAS Humanoids, 2023

    Yasunori Toshimitsu, Benedek Forrai, et al.

    Adaptive dexterous manipulation for ball rolling tasks with soft robotic systems.

  8. Vision-controlled jetting for composite systems and robots

    Nature, 2023

    Thomas J. K. Buchner, Simon Rogler, et al.

    Vision-driven control and optimization for ink-jet based manufacturing.