Papers
11
Total Citations
117
H-Index
6
About
Pian Yu is a robotics and control systems researcher whose work sits at the intersection of formal methods, multi-robot coordination, and human-robot collaboration. With a growing citation record exceeding 115 citations, Yu has established herself as a compelling voice in the design of intelligent, provably correct robotic systems. Yu's most influential contribution — "Distributed Motion Coordination for Multirobot Systems Under LTL Specifications" (2021, 36 citations) — addresses one of robotics' core challenges: enabling groups of robots to navigate shared environments safely and efficiently using Linear Temporal Logic (LTL) as a formal specification language. This thread of formal methods-driven planning runs throughout her portfolio, from robust self-triggered control under uncertainty (2019, 20 citations) to Signal Temporal Logic synthesis and ROS-based human-in-the-loop frameworks for real-world deployment. Equally notable is Yu's sustained engagement with human-robot collaboration, including trust-aware motion planning and co-adaptive systems, with her COIN project survey attracting 16 citations. Her more recent work on safe POMDP planning using conformal prediction reflects a forward-looking embrace of uncertainty-aware decision-making. Spanning precision agriculture to dynamic multi-agent environments, Yu's research consistently bridges theoretical rigor with practical robotic application.
Research Focus
Key Achievements
Top Papers
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- 3Co-adaptive Human–Robot Cooperation: Summary and Challenges16 citations · 2021
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