Papers
13
Total Citations
567
H-Index
9
About
Yushu Yu is a leading researcher in aerial robotics and human-robot interaction, whose work bridges the gap between unmanned aerial systems and intuitive control interfaces. With over 220 citations for their landmark review on computer vision-based hand gesture recognition for HRI, Yu has fundamentally advanced how humans can naturally command robots through visual cues. Their pioneering contributions to small-scale rotorcraft unmanned robotic systems (SRURSs) are equally impactful, with a highly-cited 2018 review (141 citations) establishing foundational knowledge in aerial manipulation. Yu’s innovative multipropeller multifunction aerial robot (MMAR) represents a breakthrough in multi-modal locomotion, capable of flying, wall-climbing, and arm-operating—a concept explored across multiple papers including their 2012 work on motion planning and stabilization (54 citations). More recently, Yu has pushed boundaries in intelligent control, developing deep reinforcement learning approaches for variable admittance interaction control of UAVs (2023) and multi-agent visual-inertial localization for integrated aerial systems (2024). Their research consistently addresses real-world challenges in safe landing, attitude tracking, and hybrid locomotion, making Yu a pivotal figure in shaping the future of autonomous aerial systems that can seamlessly interact with both humans and complex environments.
Research Focus
Key Achievements
Top Papers
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- 4Attitude tracking control of a quadrotor UAV in the exponential coordinates49 citations · 2013
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- 8Safe Landing Analysis of a Quadrotor Aircraft With Two Legs12 citations · 2014
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