Yuwan Gu

Changzhou University

Papers

5

Total Citations

107

H-Index

4

About

Yuwan Gu is a robotics researcher whose work bridges deep reinforcement learning and agricultural automation, with a focus on intelligent path planning and fruit harvesting. Gu’s most influential contribution, “DM-DQN: Dueling Munchausen deep Q network for robot path planning” (2022, 49 citations), introduces a novel algorithm that enhances mobile robot navigation in complex environments by integrating scaled log-policy into the reward structure, significantly improving decision-making and collision avoidance. This work is complemented by “D3-TD3: Deep Dense Dueling Architectures in TD3 Algorithm for Robot Path Planning Based on 3D Point Cloud” (2023, 6 citations), which addresses convergence issues in continuous control tasks. In agricultural robotics, Gu’s “A method to obtain the near-large fruit from apple image in orchard for single-arm apple harvesting robot” (2019, 37 citations) provides a practical solution for fruit detection and selection, while “An image rendering-based identification method for apples with different growth forms” (2023, 13 citations) advances vision-based recognition under varied conditions. Gu’s research demonstrates a clear trajectory from theoretical algorithm development to real-world deployment, with applications in both industrial automation and precision agriculture.

Research Focus

Key Achievements

4
H-Index
5
Papers
107
Total Citations
21
Avg Citations/Paper
🏆 Most Cited Paper
DM-DQN: Dueling Munchausen deep Q network for robot path planning
49 citations · 2022
📈 Most Prolific Year: 2022 (2 Papers)
🤝 Key Collaborators: 18
🏛 Institutions: Changzhou University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago