Yunhao Li

About

Yunhao Li is a roboticist whose work sits at the intersection of dynamic locomotion, reinforcement learning, and real-world robot manipulation. His most prominent contribution is the development of a reinforcement learning framework that enables quadrupedal robots to perform soccer goalkeeping—a task that demands both high-speed, agile movement and precise, non-prehensile ball manipulation. This work, published in 2023 and already garnering 36 citations, demonstrates how learned policies can bridge the gap between simulation and complex, dynamic real-world environments. By tackling the challenge of combining rapid locomotion with reactive object interaction, Li has advanced the field of legged robotics, showing that quadrupeds can be trained to handle tasks previously reserved for more specialized platforms. His research is particularly notable for its practical approach to deploying RL in the physical world, offering a blueprint for future work in agile, interactive robots. For students and researchers interested in the frontier of learning-based control for dynamic systems, Li’s work provides a compelling case study in how to push the boundaries of what legged robots can achieve.

Research Focus

Key Achievements

Top Papers

1. 1
   Creating a Dynamic Quadrupedal Robotic Goalkeeper with Reinforcement Learning

   36 citations · 2023

Key Collaborators

Contact & Links