Yuanzhe Cui

Tongji University

Papers

6

Total Citations

65

H-Index

3

About

Yuanzhe Cui is a leading researcher in multi-robot systems and intelligent manipulation, with a focus on closed-chain control, deep reinforcement learning (DRL), and cooperative robotics. His most cited work, a 2024 study on a task-adaptive DRL framework for dual-arm robot manipulation (46 citations), addresses the complex challenge of closed-chain coordination, enabling flexible and adaptable control for cooperative tasks. Cui has also made significant contributions to multi-mobile manipulator systems, including coordinated control under closed-chain constraints and distributed position-force control for cooperative transportation, advancing the field's understanding of dynamic coupling between mobile platforms and robotic arms. His research extends to multi-robot SLAM through map fusion via image stitching, and to bio-inspired systems, where he models collective dynamics and visual interaction topologies for flapping-wing robot flocks. With a total of over 65 citations across his most-cited papers, Cui's work is foundational for developing robust, adaptive robotic teams capable of complex real-world manipulation and exploration.

Research Focus

Key Achievements

3
H-Index
6
Papers
65
Total Citations
11
Avg Citations/Paper
🏆 Most Cited Paper
A Task-Adaptive Deep Reinforcement Learning Framework for Dual-Arm Robot Manipulation
46 citations · 2024
📈 Most Prolific Year: 2021 (4 Papers)
🤝 Key Collaborators: 12
🏛 Institutions: Tongji University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago