Jianrui Du
Papers
3
Total Citations
22
H-Index
3
About
Jianrui Du is a leading researcher in aerial robotics, specializing in the intersection of control, perception, and machine learning for autonomous systems. His primary contributions lie in developing intelligent interaction control for unmanned aerial vehicles (UAVs) and creating high-fidelity simulation environments for complex aerial platforms. Du’s most influential work, "Variable Admittance Interaction Control of UAVs via Deep Reinforcement Learning" (2023, 10 citations), introduces a novel reinforcement learning-based admittance model that enables UAVs to autonomously adapt their force control during physical interactions with the environment—a critical advancement for tasks like manipulation and contact-based inspection. He further advances the field with his simulation frameworks: "High-Fidelity Integrated Aerial Platform Simulation for Control, Perception, and Learning" (2025, 7 citations) and "AeroBotSim: A High-Photo-Fidelity Simulator for Heterogeneous Aerial Systems Under Physical Interaction" (2023, 5 citations). These tools prioritize photorealistic rendering and contact fidelity, supporting diverse multi-rotor configurations and enabling robust testing of control and perception algorithms under realistic physical interaction scenarios. Du’s work is foundational for bridging the gap between simulation and real-world deployment in aerial robotics.
Research Focus
Key Achievements
Top Papers
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