Papers
1
Total Citations
11
H-Index
1
About
Xiaohai Yin’s research focuses on intelligent robotics and autonomous navigation, particularly for critical infrastructure applications like power system maintenance. His most impactful work addresses the challenge of path planning for mobile robots in complex environments, such as ultra-high voltage (UHV) substations. Yin’s major contribution is a novel hybrid algorithm that combines an enhanced Artificial Potential Field (APF) method with an improved Ant Colony Optimization (ACO) algorithm. This approach overcomes the limitations of traditional path planning methods, enabling robots to navigate more safely and efficiently in constrained, hazardous settings. His 2023 paper on this topic has already garnered 11 citations, signaling its relevance for researchers in robotics and power engineering. By developing practical solutions for emergency maintenance scenarios, Yin’s work bridges the gap between theoretical robotics and real-world industrial needs, offering a foundation for future autonomous systems in energy infrastructure.
Research Focus
Key Achievements
Top Papers
- 1