Airong Wei
Papers
1
Total Citations
12
H-Index
1
About
Airong Wei is a robotics researcher whose work centers on bio-inspired robotic systems and intelligent control, with a particular focus on robotic fish. Her key contributions lie at the intersection of reinforcement learning, imitation learning, and pose regulation—addressing the challenging problem of enabling underwater robots to autonomously reach a target position with precise orientation. In her highly regarded 2022 paper, "Leveraging Imitation Learning on Pose Regulation Problem of a Robotic Fish," Wei innovatively reformulated this dual-objective control task as a Markov decision process (MDP), demonstrating how imitation learning can effectively guide a robotic fish to converge on both location and heading. This work, which has garnered 12 citations, tackles a fundamental hurdle in underwater robotics: balancing positional accuracy with directional control in a dynamic fluid environment. By bridging model-free learning with classical control objectives, Wei’s research offers a scalable framework for agile, autonomous underwater vehicles. Her contributions are particularly impactful for students and researchers exploring the intersection of machine learning and physical robotics, providing a practical pathway toward more intelligent and adaptable bio-inspired systems.
Research Focus
Key Achievements
Top Papers
- 1Leveraging Imitation Learning on Pose Regulation Problem of a Robotic Fish12 citations · 2022