Yuting Feng
Papers
2
Total Citations
15
H-Index
2
About
Yuting Feng is a researcher at the forefront of aerial robotics and autonomous interaction control. Her work centers on enabling unmanned aerial vehicles (UAVs) to perform complex physical tasks through intelligent, adaptive control systems. Feng’s major contributions include pioneering the use of deep reinforcement learning for variable admittance interaction control, allowing drones to autonomously adjust their compliance during physical contact with the environment—a critical capability for tasks like inspection, manipulation, and assembly. Her 2023 paper on this topic has garnered 10 citations, reflecting its significance in advancing force control for aerial systems. Additionally, she developed AeroBotSim, a high-photo-fidelity simulator designed for heterogeneous aerial systems under physical interaction, which provides researchers with a realistic platform for testing and validating interaction algorithms. This work, with 5 citations, underscores her commitment to bridging simulation and real-world deployment. Feng’s research is shaping the next generation of autonomous aerial robots that can safely and effectively collaborate with humans and their surroundings.
Research Focus
Key Achievements
Top Papers
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