Jiabao Wen
Papers
2
Total Citations
162
H-Index
2
About
Jiabao Wen is a leading researcher in intelligent robotics, specializing in the application of reinforcement learning to autonomous navigation in complex, real-world environments. His work focuses on solving critical challenges in path planning for both underwater and agricultural robots, where dynamic and unpredictable conditions—such as unknown obstacles in the deep sea or variable terrain in farmlands—demand adaptive, real-time decision-making. Wen’s most influential paper, “Intelligent Path Planning of Underwater Robot Based on Reinforcement Learning” (2022), has garnered 97 citations, demonstrating its significant impact on advancing autonomous underwater vehicle capabilities. His follow-up study, “The Intelligent Path Planning System of Agricultural Robot via Reinforcement Learning” (2022), with 65 citations, extends these principles to agricultural modernization, integrating artificial intelligence with Internet of Things (IoT) technologies to enhance farming efficiency. Together, these works establish Wen as a key contributor to the field of intelligent robotics, bridging theoretical reinforcement learning with practical, high-stakes applications. His research continues to inspire innovations in autonomous systems, offering scalable solutions for industries requiring robust, self-learning navigation.
Research Focus
Key Achievements
Top Papers
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