Papers
1
Total Citations
13
H-Index
1
About
You Teng is a researcher specializing in distributed control systems and multi-robot coordination, with a particular focus on formation control and optimization strategies. Their most-cited work, "Nash-optimization distributed model predictive control for multi mobile robots formation" (2016), has garnered 13 citations, showcasing their contribution to advancing decentralized decision-making in robotics. This paper introduces a novel approach that integrates game theory with model predictive control, enabling multiple mobile robots to achieve stable formations through Nash equilibrium-based optimization—a key innovation for applications like autonomous swarms and collaborative exploration. Teng’s research bridges theoretical control methods with practical robotics, addressing challenges in scalability and real-time performance. Their work is notable for its emphasis on distributed architectures, which reduce communication overhead and enhance robustness in dynamic environments. By combining predictive control with game-theoretic principles, Teng has provided a framework that inspires further studies in multi-agent systems, particularly for tasks requiring coordinated motion without centralized supervision. This contribution remains relevant for students and researchers exploring autonomous systems, offering a foundation for scalable, efficient formation control in robotics.
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