Hongxin Xue
Papers
1
Total Citations
26
H-Index
1
About
Hongxin Xue is a rising researcher in the field of robotics and artificial intelligence, with a focused expertise in intelligent path planning and deep reinforcement learning (DRL). Their most-cited work, "Improved Robot Path Planning Method Based on Deep Reinforcement Learning" (2023), has garnered 26 citations, marking a significant early-career contribution. In this study, Xue tackles the complex, nonlinear challenge of robot navigation by enhancing the Deep Q-Network (DQN) algorithm, demonstrating how DRL can achieve more efficient and adaptive path planning in dynamic environments. This work not only advances the theoretical understanding of DRL applications in robotics but also offers practical improvements for autonomous systems. Xue’s research bridges the gap between algorithmic innovation and real-world robotic deployment, making their contributions valuable for students and engineers seeking to implement smarter, self-learning navigation systems. With a growing citation footprint, Hongxin Xue is establishing themselves as a promising voice in the integration of AI and robotics.
Research Focus
Key Achievements
Top Papers
- 1Improved Robot Path Planning Method Based on Deep Reinforcement Learning26 citations · 2023