Yanqi Chen

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About

Yanqi Chen is a robotics researcher whose work focuses on advancing autonomous navigation in complex, dynamic environments. Chen’s primary research areas include mobile robot path planning, artificial potential fields, and cellular neural networks. Their most notable contribution is an improved real-time path planning algorithm that integrates cellular neural networks with the artificial potential field concept, addressing a critical limitation of traditional methods that fail to adapt to unpredictable surroundings. By ensuring the target neuron holds the maximal positive value, Chen’s approach enhances a robot’s ability to navigate safely and efficiently in real time. While this foundational work has garnered 2 citations, it represents an important step toward more responsive and intelligent robotic systems. Chen’s research is particularly valuable for applications in autonomous vehicles, warehouse logistics, and search-and-rescue operations, where adaptability is key. Their work continues to inspire further developments in neural network-based navigation, offering a promising direction for students and researchers interested in bridging the gap between theoretical control systems and practical robotic deployment.