Papers
2
Total Citations
12
H-Index
2
About
Tingqi Zhang is a researcher whose work focuses on the intersection of multi-robot systems and intelligent manufacturing, with a particular emphasis on collision avoidance and scheduling in complex industrial environments. Their key research areas include heterogeneous multi-mobile robot systems (MMRSs), automated guided vehicle (AGV) scheduling, and assembly line optimization. Zhang’s major contributions lie in developing novel algorithms for managing robot fleets in dynamic settings—such as the "glued nodes" approach for collision avoidance among variable-sized robots, and a look-ahead scheduling algorithm that ensures processing sequence conflict-free operation on no-buffer assembly lines. These innovations address critical challenges in modern workshops and storage facilities, where customized production demands flexible, efficient automation. With over 12 citations across their most-cited works, Zhang’s research is gaining traction among peers in robotics and industrial engineering. Their notable achievements include tackling the complex problem of heterogeneous robot coordination and providing practical solutions for real-world manufacturing constraints. For students and researchers exploring the future of smart factories, Zhang’s work offers a compelling blend of theoretical rigor and applied problem-solving.
Research Focus
Key Achievements
Top Papers
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- 2