Dongho Kang

About

Dongho Kang is a robotics researcher specializing in legged locomotion, motion control, and the integration of reinforcement learning with model-based optimization for quadrupedal robots. His work sits at the intersection of control theory, machine learning, and biomechanics-inspired robotics, pushing the boundaries of how robots can move with animal-like agility and naturalness. Kang's most influential contribution, "RL + Model-Based Control" (2023, 35 citations), introduces a hybrid framework that leverages on-demand optimal control to enrich reinforcement learning training, yielding versatile and robust locomotion behaviors. This theme of combining data-driven and physics-based methods runs throughout his research: earlier work demonstrated how motion matching and nonlinear model predictive control (NMPC) can reproduce authentic animal gaits on real hardware (2021–2022, 18–14 citations). His control-aware design optimization approach further bridges the gap between robot morphology and controller performance, enabling gradient-based co-design of quadrupedal systems. More recently, Kang has expanded into compliant control for natural disturbance recovery and loco-manipulation, where robots must simultaneously locomote and interact with objects. With over 100 cumulative citations and a growing portfolio of impactful publications, Kang is establishing himself as a leading voice in next-generation legged robot control.

Research Focus

Key Achievements

Top Papers

1. 1
   RL + Model-Based Control: Using On-Demand Optimal Control to Learn Versatile Legged Locomotion

   35 citations · 2023
2. 2
   Animal Gaits on Quadrupedal Robots Using Motion Matching and Model-Based Control

   18 citations · 2021
3. 3
   Control-Aware Design Optimization for Bio-Inspired Quadruped Robots

   15 citations · 2021
4. 4
   Animal Motions on Legged Robots Using Nonlinear Model Predictive Control

   14 citations · 2022
5. 5
   Deep Compliant Control for Legged Robots

   8 citations · 2024
6. 6
   2-D cooperative localization with omni-directional mobile robots

   6 citations · 2015
7. 7
   Rambo: RL-Augmented Model-Based Whole-Body Control for Loco-Manipulation

   2 citations · 2025
8. 8
   Spatio-Temporal Motion Retargeting for Quadruped Robots

   2 citations · 2025

Key Collaborators

Contact & Links