Papers

2

Total Citations

153

H-Index

2

About

Nicole Hurley is a leading researcher in robotics and artificial intelligence, specializing in the intersection of deep reinforcement learning and agile locomotion for humanoid robots. Her groundbreaking work focuses on enabling low-cost, miniature bipedal robots to master complex, dynamic behaviors that were previously thought to require expensive, high-end hardware. Hurley’s most influential contribution is her 2024 study on learning agile soccer skills for a bipedal robot, which has garnered 147 citations. In this work, she demonstrated that deep RL could synthesize sophisticated and safe movement skills—such as rapid direction changes, ball dribbling, and coordinated tackling—for a 20-actuator humanoid, allowing it to play a simplified one-versus-one soccer match. This achievement proved that complex, real-time strategies could emerge from simulation-trained policies, bridging the gap between virtual training and physical deployment. Her earlier 2023 paper (6 citations) laid the foundational framework for this approach. Hurley’s research has profound implications for robotics, from disaster response to assistive technologies, and her work is celebrated for making advanced humanoid agility accessible and scalable.

Research Focus

Key Achievements

2
H-Index
2
Papers
153
Total Citations
77
Avg Citations/Paper
🏆 Most Cited Paper
Learning agile soccer skills for a bipedal robot with deep reinforcement learning
147 citations · 2024
📈 Most Prolific Year: 2024 (1 Papers)
🤝 Key Collaborators: 27
🏛 Institutions: Google DeepMind (United Kingdom), University College London

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago