Hongfang Sun
Papers
1
Total Citations
24
H-Index
1
About
Hongfang Sun is a leading researcher in intelligent robotics and autonomous navigation, with a particular focus on reinforcement learning for dynamic environments. Her most cited work, "Research on Dynamic Path Planning of Mobile Robot Based on Improved DDPG Algorithm" (2021, 24 citations), addresses critical limitations in deep reinforcement learning for real-world robotics. Sun introduced a novel approach that replaces the standard neural network optimizer in the Deep Deterministic Policy Gradient (DDPG) algorithm with the RAdam optimizer, significantly improving both learning speed and task success rates in unpredictable settings. This contribution has been widely recognized for bridging the gap between theoretical reinforcement learning and practical mobile robot deployment. Beyond this flagship study, Sun's research portfolio consistently explores adaptive control strategies and sensor fusion for autonomous systems. Her work has garnered attention from both academic and industrial robotics communities, with citations reflecting its relevance to ongoing challenges in safe and efficient path planning. Sun continues to advance the field by developing algorithms that enable robots to make real-time decisions in cluttered or moving environments, marking her as an influential voice in the next generation of intelligent autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1