Chuanbeibei Shi

Beijing Institute of Technology

Papers

2

Total Citations

19

H-Index

2

About

Chuanbeibei Shi is advancing the frontier of autonomous aerial robotics, with a focus on intelligent interaction control and multi-agent localization. Her work bridges reinforcement learning and adaptive control, most notably through a 2023 study proposing a variable admittance interaction controller for UAVs. By training a deep reinforcement learning policy to dynamically adjust compliance, her model enables drones to autonomously execute force-sensitive tasks—such as physical contact with environments—with unprecedented adaptability. This paper has garnered 10 citations and represents a significant step toward robots that can safely and effectively interact with the world. In 2024, Shi tackled the challenge of relative pose estimation in Integrated Aerial Platforms (IAPs), where multiple UAV agents are physically connected. Her multi-agent visual-inertial localization framework, which loosely fuses odometry with kinematic constraints, provides reliable global localization for these complex systems—a problem distinct from free-flying swarms. With 9 citations, this work is foundational for coordinated, tethered aerial operations. Shi’s research is shaping the next generation of autonomous systems that can both reason about their environment and physically collaborate with it.

Research Focus

Key Achievements

2
H-Index
2
Papers
19
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Variable Admittance Interaction Control of UAVs via Deep Reinforcement Learning
10 citations · 2023
📈 Most Prolific Year: 2023 (1 Papers)
🤝 Key Collaborators: 9
🏛 Institutions: Beijing Institute of Technology

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 12 days ago