Xucan Chen

National University of Defense Technology

Papers

Total Citations

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About

Xucan Chen is a researcher specializing in bio-inspired robotics and distributed artificial intelligence, with a primary focus on underwater robotic systems. Their most notable contribution lies in the numerical simulation and analysis of fish-like robot swarms, a 2019 study that has garnered 28 citations and addresses the critical gap between single-robot mechanism behavior and the complex hydro-environmental influences on collective robotic crowds. This work provides foundational insights into swarm dynamics, challenging existing assumptions about underwater robot coordination. Chen has also explored advanced machine learning techniques, developing a distributed reinforcement learning framework that incorporates state feature encoding and stacking for continuous action spaces—a 2021 contribution that pushes the boundaries of autonomous decision-making in multi-agent systems. By bridging computational fluid dynamics with swarm intelligence, Chen’s research offers practical pathways for designing more efficient, adaptive underwater exploration and monitoring platforms. Their work is particularly relevant for students and researchers interested in the intersection of robotics, reinforcement learning, and environmental interaction, demonstrating how simulation-driven approaches can unlock new capabilities in autonomous underwater vehicles.