Papers
1
Total Citations
3
H-Index
1
About
Mingke Gao’s research focuses on path planning and terrain analysis for robotics and autonomous navigation. In their most-cited work, “Improved Path Planning Algorithm on the Rugged Road” (2016), Gao introduced a 2.5-dimensional terrain grid that significantly reduces computational load for navigation in uneven environments. By integrating fuzzy logic theory, the algorithm evaluates terrain trafficability, enabling more efficient and realistic path selection across rugged roads. Although the paper has garnered 3 citations, it represents a foundational step in bridging computational efficiency with real-world terrain complexity. Gao’s contributions are particularly relevant to robotics, game development, and group animation, where dynamic path planning on non-flat surfaces remains a critical challenge. Their work demonstrates a practical approach to balancing accuracy and speed, offering a scalable solution for autonomous systems operating in unstructured outdoor settings. As a researcher, Gao continues to explore how intelligent algorithms can improve mobility and decision-making in complex terrains, with potential applications in field robotics and simulation.
Research Focus
Key Achievements
Top Papers
- 1Improved Path Planning Algorithm on the Rugged Road3 citations · 2016