DONGHO KANG

Legged robotics, character animation, optimal control, and reinforcement learning

profile.jpg

Wasserwerkstrasse 12

8092 Zurich

Switzerland

I am a doctoral student in computer science based in Zurich, Switzerland 🇨🇭. From 2019, I am a scientific assistant of the Computational Robotics Lab, ETH Zurich, under the supervision of Prof. Stelian Coros.

The goal of my research is to create legged robots that exhibit natural and animal-like behaviors. Thus, my research interests are broad ranging from legged locomotion control to computational methods for motion and behavior synthesys.

Apart from my professional bio, I am originally from Seoul, South Korea 🇰🇷. Describing myself, I am a fan of video games, sci-fi movies and a classical music lover.

news

Apr 18, 2024 Introducing my recent collaboration work, “Spatio-Temporal Motion Retargeting for Quadruped Robots”, co-authored with Taerim Yoon, Seungmin Kim, Minsung Ahn, Prof. Stelian Coros, and Prof. Sungjoon Choi. Visit the project website to learn more.
Jan 29, 2024 My recent collaborative work titled “Deep Compliant Control for Legged Robots,” co-authored with Adrian Hartmann, Fatemeh Zargarbashi, Miguel Angel Zamora Mora, and Prof. Stelian Coros, has been accepted to 2024 IEEE International Conference on Robotics and Automation (ICRA 2024)!
Oct 16, 2023 My recent collaborative work titled “Tuning Legged Locomotion Controllers via Safe Bayesian Optimization,” co-authored with Daniel Widmer, Bhavya Sukhija, and Jonas Hübotter, under the guidance of Prof. Andreas Krause and Prof. Stelian Coros, has been accepted to the 7th Annual Conference on Robot Learning (CoRL 2023)! Visit the project website to learn more.
Aug 23, 2023 We present our latest work, “RL + Model-based Control: Using On-demand Optimal Control to Learn Versatile Legged Locomotion”. The paper is published to the IEEE Robotics and Automation Letters (RA-L) journal. To learn more about the paper, please visit the project website.
Jun 30, 2022 I am happy to announce my paper, "Animal Motions on Legged Robots Using Nonlinear Model Predictive Control" has been accepted to 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS 2022).

selected publications

2024

  1. zargarbashi2024robot.png
    RobotKeyframing: Learning Locomotion with High-Level Objectives via Mixture of Dense and Sparse Rewards
    Fatemeh Zargarbashi, Jin Cheng, Dongho Kang, and 2 more authors
    2024
  2. yoon2024spatiotemporal.png
    Spatio-Temporal Motion Retargeting for Quadruped Robots
    Taerim Yoon, Dongho Kang, Seungmin Kim, and 3 more authors
    2024
  3. hartmann2024deep.png
    Deep Compliant Control for Legged Robots
    Adrian Hartmann, Dongho Kang, Fatemeh Zargarbashi, and 2 more authors
    In 2024 IEEE International Conference on Robotics and Automation (ICRA), 2024

2023

  1. widmer2023tuning.png
    Tuning Legged Locomotion Controllers via Safe Bayesian Optimization
    Daniel Widmer, Dongho Kang, Bhavya Sukhija, and 3 more authors
    In Proceedings of The 7th Conference on Robot Learning, 2023
  2. kang2023rl.png
    RL + Model-Based Control: Using On-Demand Optimal Control to Learn Versatile Legged Locomotion
    Dongho Kang, Jin Cheng, Miguel Zamora, and 2 more authors
    IEEE Robotics and Automation Letters, 2023

2022

  1. kang2022animal.png
    Animal Motions on Legged Robots Using Nonlinear Model Predictive Control
    Dongho Kang, Flavio De Vincenti, Naomi C. Adami, and 1 more author
    In 2022 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2022

2021

  1. kang2021animal.png
    Animal Gaits on Quadrupedal Robots Using Motion Matching and Model-Based Control
    Dongho Kang, Simon Zimmermann, and Stelian Coros
    In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021
  2. devincenti2021control.png
    Control-Aware Design Optimization for Bio-Inspired Quadruped Robots
    Flavio De Vincenti, Dongho Kang, and Stelian Coros
    In 2021 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2021