Jinwei Yu
Papers
2
Total Citations
5
H-Index
2
About
Jinwei Yu is an emerging researcher specializing in distributed control systems, multi-robot coordination, and intelligent control of robotic systems. Their work sits at the intersection of control theory, robotics, and machine learning, with a particular focus on formation control for complex multi-agent systems operating under real-world uncertainties. Yu's most notable contributions include pioneering approaches to coordinating multiple redundant robot manipulators using potential energy frameworks, enabling robust region-tracking formation control in distributed settings. Complementing this, their neural network-based methodology for controlling multiple nonholonomic mobile robots addresses the challenging problem of uncertain kinematics and dynamics — a critical barrier to deploying autonomous robot teams in unpredictable environments. By leveraging adaptive neural networks within distributed architectures, Yu's work offers practical pathways toward more resilient and scalable multi-robot systems. Although Yu's publication record is in its early stages, with their 2025 papers already accumulating citations from the research community, the work demonstrates strong foundational promise. Students and researchers working in autonomous systems, swarm robotics, or adaptive control will find Yu's contributions highly relevant to advancing the theoretical and applied frontiers of intelligent multi-robot coordination.
Research Focus
Key Achievements
Top Papers
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- 2