Papers
20
Total Citations
241
H-Index
8
About
Qingchen Liu is a leading researcher in multi-robot systems, safe autonomous navigation, and human-robot interaction, with a focus on bridging control theory and machine learning. His most influential work includes a highly cited 2018 paper on circular formation algorithms for nonholonomic mobile robots (46 citations), which established foundational optimization-based approaches for multi-agent coordination. Liu has made major contributions to mapless navigation, notably developing safety-enhanced imitation learning (32 citations) and socially aware multi-agent algorithms like SRL-ORCA (21 citations) that enable robots to navigate complex dynamic environments without maps. He has advanced privacy-preserving distributed localization for wireless sensor networks (25 citations) and introduced game-theoretic frameworks for safe human-swarm interaction (20 citations) and nonlinear human-robot interaction systems (12 citations). His recent work on uncertainty-separated control barrier functions (15 citations) provides robust safety guarantees in unknown environments, while his slip detection and recovery system for quadruped robots (7 citations) addresses real-world locomotion challenges. With over 190 total citations across his top papers, Liu’s research consistently tackles fundamental challenges in safe, scalable, and socially aware autonomous systems, making him a rising figure in robotics and control.
Research Focus
Key Achievements
Top Papers
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- 2Mapless Navigation With Safety-Enhanced Imitation Learning32 citations · 2022
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