Yuwen Zhou

Fujian University of Technology, University of Bristol

Papers

Total Citations

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About

Yuwen Zhou is an emerging researcher in robotics and intelligent systems, with a focused interest in autonomous navigation, low-cost automation, and the integration of Internet of Things (IoT) technologies with renewable energy. Zhou’s most cited work, “Shortest Distance Maze Solving Robot” (2020, 6 citations), introduces a low-cost, autonomous robot that combines wall tracking and flood fill algorithms to navigate mazes without human intervention, demonstrating a practical approach to embedded intelligence. This study highlights Zhou’s ability to merge algorithmic efficiency with hardware accessibility. Expanding into smart home applications, Zhou’s 2021 paper on IoT-based control powered by photovoltaic cells (2 citations) explores sustainable, cost-effective automation. Most recently, in 2025, Zhou proposed an end-to-end robot obstacle avoidance method using deep reinforcement learning with a spatiotemporal transformer architecture (1 citation), aiming to enhance decision-making in complex dynamic environments. Though early in their career, Zhou’s work bridges classical robotics algorithms with modern deep learning techniques, offering scalable solutions for autonomous systems. Their research trajectory—from maze solving to intelligent obstacle avoidance—reflects a commitment to advancing robot autonomy through both algorithmic innovation and practical, low-cost design.