Papers

2

Total Citations

88

H-Index

2

About

Kui Xiao is a leading researcher in robotics and intelligent control systems, with a primary focus on path planning and trajectory optimization for mobile robots operating in complex environments. Their major contributions lie in developing advanced algorithms that enhance robot navigation efficiency and safety. Notably, Xiao proposed a cubic spline interpolation-based path planning method integrated with a chaotic adaptive particle swarm optimization algorithm, which ensures smooth and collision-free robot movement—a work that has garnered 76 citations for its practical significance. Additionally, Xiao introduced the mutual learning and adaptive ant colony optimization (MuL-ACO) algorithm for trajectory generation in uneven terrains, addressing the challenge of dynamic obstacles and irregular surfaces. This innovative approach, published in 2022, has already attracted 12 citations, reflecting its growing impact. Xiao’s research bridges theoretical optimization with real-world robotic applications, offering robust solutions for autonomous navigation. Their work is widely recognized for improving computational efficiency and adaptability, making them a notable figure in the field of robotics and artificial intelligence.

Research Focus

Key Achievements

2
H-Index
2
Papers
88
Total Citations
44
Avg Citations/Paper
🏆 Most Cited Paper
Cubic Spline Interpolation-Based Robot Path Planning Using a Chaotic Adaptive Particle Swarm Optimization Algorithm
76 citations · 2020
📈 Most Prolific Year: 2020 (1 Papers)
🤝 Key Collaborators: 6
🏛 Institutions: Central South University of Forestry and Technology

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago