Ni Bin
Papers
2
Total Citations
31
H-Index
2
About
Dr. Ni Bin has made foundational contributions to intelligent robotics, particularly in the domain of autonomous navigation and path planning. His pioneering work on applying recurrent neural networks to robot motion control established a novel framework for real-time obstacle avoidance in unknown environments. His most influential paper, "Recurrent Neural Network for Robot Path Planning" (2004), has garnered 26 citations, demonstrating its lasting impact on the field. In a subsequent study, Dr. Bin introduced a topologically ordered neural network model that enables robots to navigate autonomously using only limited local information—neighbor positions and target distance—rather than requiring a complete global map. This approach proved remarkably effective for path planning and obstacle avoidance in uncharted terrains. By bridging neural computation with robotic autonomy, Dr. Bin’s work has informed subsequent research in mobile robotics, swarm intelligence, and adaptive control systems. His contributions remain a valuable reference for engineers and researchers developing intelligent, self-guided robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Recurrent Neural Network for Robot Path Planning26 citations · 2004
- 2New approach of neural network for robot path planning5 citations · 2005