Xiaoyi Deng

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About

Xiaoyi Deng is a researcher in autonomous systems and robotics, with a primary focus on unmanned aerial vehicle (UAV) navigation and intelligent path planning. Their most cited work, "Path planning for indoor UAV based on Ant Colony Optimization" (2013, 43 citations), represents a significant contribution to the field of autonomous navigation. In this study, Deng applied bio-inspired Ant Colony Optimization algorithms to solve the complex problem of finding optimal flight paths for UAVs in constrained indoor environments—a critical challenge for applications ranging from search-and-rescue to infrastructure inspection. By adapting swarm intelligence techniques to the specific demands of indoor UAV navigation, Deng demonstrated how nature-inspired algorithms can effectively handle the trade-offs between path length, obstacle avoidance, and computational efficiency. This work has provided a foundational framework for subsequent research in autonomous indoor flight, influencing both academic studies and practical UAV system designs. Deng's research continues to bridge the gap between theoretical optimization methods and real-world robotic applications, making their contributions particularly valuable for engineers and researchers developing next-generation autonomous aerial systems.