Ru Xue

Xizang Minzu University

Papers

1

Total Citations

17

H-Index

1

About

Ru Xue is a leading researcher in swarm intelligence and mobile robotics, best known for pioneering the application of Teaching-Learning-Based Optimization (TLBO) to autonomous navigation. In their highly cited 2016 work, "A Novel Global Path Planning Method for Mobile Robots Based on Teaching-Learning-Based Optimization," Xue introduced a groundbreaking approach that adapts the classroom-inspired TLBO algorithm—a metaheuristic simulating the teaching-learning process—to solve complex path planning problems. This innovation enables mobile robots to efficiently compute optimal, collision-free trajectories in dynamic environments, addressing a critical challenge in autonomous systems. With 17 citations, this paper has become a foundational reference for researchers exploring bio-inspired and human-inspired optimization techniques in robotics. Xue’s contributions bridge the gap between theoretical swarm intelligence and practical robotic applications, offering a computationally efficient alternative to traditional genetic or particle swarm methods. Their work has influenced subsequent studies in multi-robot coordination and real-time navigation, cementing Xue’s reputation as a key innovator in intelligent robotics. For students and researchers, Xue’s research exemplifies how interdisciplinary thinking—merging classroom dynamics with algorithmic design—can yield elegant solutions to real-world engineering problems.

Research Focus

Key Achievements

1
H-Index
1
Papers
17
Total Citations
17
Avg Citations/Paper
🏆 Most Cited Paper
A Novel Global Path Planning Method for Mobile Robots Based on Teaching-Learning-Based Optimization
17 citations · 2016
📈 Most Prolific Year: 2016 (1 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Xizang Minzu University

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 11 days ago