Jonas Frey

Robotic Systems Lab - ETH Zurich / Max Planck Institute

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I am doing my Ph.D. in robotics at the Robotic Systems Lab at ETH Zurich and the Max Planck Institute for Intelligent Systems, co-advised by Marco Hutter and Georg Martius. My research focuses on Learning Perception and Navigation for Legged Robots.

During my Bachelor’s, I worked at the chair for High Performance Humanoid Technologies with Prof. Tamim Asfour (KIT, Germany) and conducted my Bachelor’s Thesis with Prof. Takamitsu Matsubara in Japan (NAIST, Japan). I worked as a Collaborative Robotics Engineer at SEW-Eurodrive before starting my Master’s in Robotics Systems and Control at ETH Zurich. Throughout my Master’s I was supervised by Prof. Roland Siegwart and spent most of my time at the Autonmous Systems Lab.

During my Ph.D. I joined NASA’s Jet Propulsion Laboratory as a visiting researcher and continuously collaborate with the Dynamic Robotic Systems Group by Prof. Maurice Fallon at University of Oxford. Feel free to reach out to me! I am always happy to discuss and exchange research ideas.

news

Apr 20, 2024 Our paper “Resilient Legged Local Navigation: Learning to Traverse with Compromised Perception End-to-End,” has been nominated for the Best Paper Award for ICRA2024! Key Insights:
  • Unreliable Perception Systems: It’s impossible to always guarantee the reliability of perception systems.
  • Need for Advanced Planning: There is a critical need for planners that can detect failures in perception systems and react appropriately.
  • Use of Proprioceptive Data: Detecting these failures is feasible through the use of proprioceptive data.
  • Limitations of Traditional Methods: Classical planning methods often fail to utilize such data effectively, prompting the need for innovative solutions.
  • Using RL to Discover Emerging Navigation Strategies: Rather than relying on handcrafted heuristics, we use reinforcement learning (RL) and expose the robot to an environment with various types of perception failures. Our asymmetric actor-critic framework discovers emerging navigation strategies.
Mar 19, 2024 We’re thrilled to announce that our grant application for :sparkles: “Fostering Research on Mobile Robotics with High-Quality Data and Open Tooling” :sparkles: has been accepted! We aim to provide researchers with tailored, high-quality data for legged robots, to establish standardized benchmarks and foster the development of future algorithms. Stay tuned for updates as we advance mobile robotics research. Special thanks to Turcan Tuna, Marco Hutter, and Cesar Cadena! Learn more about the open research data initiative here. link
Dec 06, 2021 Our work: :sparkles: “Continual Learning of Semantic Segmentation using Complementary 2D-3D Data Representations” :sparkles: received the Best Paper Runner-Up Award at NeurIPS - 2021 4th Robot Learning Workshop Self-Supervised and Lifelong Learning link
Aug 31, 2021 I received my Master from ETH Zurich in Robotics Systems and Contol graduating with Summa cum Laude.

selected publications

  1. geist2024position.png
    Learning with 3D rotations, a hitchhiker’s guide to SO(3)
    A. René Geist , Jonas Frey, Mikel Zobro , and 2 more authors
    In under review for ICML , 2024
  2. frey2024roadrunner.jpg
    RoadRunner - Learning Traversability Estimation for Autonomous Off-road Driving
    Jonas Frey, Shehryar Khattak , Manthan Patel , and 5 more authors
    2024
  3. frey2023fast.jpg
    Fast Traversability Estimation for Wild Visual Navigation
    Jonas Frey, Matias Mattamala , Nived Chebrolu , and 3 more authors
    In Robotics: Science and Systems 2023 , 2023
  4. frey2022locomotion.jpg
    Locomotion policy guided traversability learning using volumetric representations of complex environments
    Jonas Frey, David Hoeller , Shehryar Khattak , and 1 more author
    In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) , 2022