Geqiang Pan
Papers
1
Total Citations
3
H-Index
1
About
Geqiang Pan is a robotics researcher whose work focuses on the challenging intersection of evolutionary computation and multi-legged robot locomotion. His primary research area is the optimization of robotic gaits—the coordinated movement patterns of legs—for navigating complex, unstructured terrains. Pan’s major contribution lies in developing an evolutionary gait transfer framework that enables multi-legged robots to adapt their locomotion strategies when transitioning between vastly different environments, such as from flat ground to rocky or uneven surfaces. This approach addresses the high-dimensional control problem inherent in multi-legged systems, where traditional optimization methods often fail. While his most-cited paper, "Evolutionary Gait Transfer of Multi-Legged Robots in Complex Terrains" (2020, 3 citations), represents foundational work in this niche, its impact is growing as the field of autonomous robotics expands. Pan’s research is notable for bridging bio-inspired evolutionary algorithms with practical robotic control, offering a scalable solution for robots operating in real-world, unpredictable settings. His work is particularly valuable for students and researchers interested in adaptive locomotion, evolutionary robotics, and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1Evolutionary Gait Transfer of Multi-Legged Robots in Complex Terrains3 citations · 2020