Yiming Ni

University of California, Berkeley

Papers

2

Total Citations

42

H-Index

2

About

Yiming Ni is a robotics researcher whose work pushes the boundaries of dynamic quadrupedal locomotion and dexterous manipulation. His primary research areas focus on applying reinforcement learning (RL) to enable highly agile, real-world behaviors in legged robots, particularly in sports and complex task execution. Ni’s most impactful contribution is his pioneering framework for creating a dynamic quadrupedal robotic goalkeeper, detailed in his 2023 paper (36 citations). This work is notable for solving the exceptionally challenging problem of combining high-speed locomotion with precise, non-prehensile ball manipulation, enabling a robot to perform real-time saves. Building on this, his 2024 paper on HiLMa-Res (6 citations) introduces a general hierarchical framework that uses residual RL to seamlessly integrate locomotion with manipulation tasks, moving beyond single-task solutions. This framework represents a significant step toward versatile, multi-purpose quadrupedal robots capable of navigating and interacting with their environment simultaneously. Ni’s research is at the forefront of creating robots that can perform with the agility and reactivity of living athletes.

Research Focus

Key Achievements

2
H-Index
2
Papers
42
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
Creating a Dynamic Quadrupedal Robotic Goalkeeper with Reinforcement Learning
36 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 14
🏛 Institutions: University of California, Berkeley

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago