Papers

2

Total Citations

19

H-Index

2

About

Liangyi Yang has made foundational contributions to multi-robot coordination and task optimization, with a focus on solving complex allocation and scheduling problems in dynamic environments. Their pioneering work, "Optimal ant colony algorithm based multi-robot task allocation and processing sequence scheduling" (2008, 14 citations), introduced a novel ant colony optimization approach that efficiently distributes tasks among limited robots while minimizing completion time—a critical challenge in industrial automation and swarm robotics. This algorithm remains a reference point for researchers tackling NP-hard scheduling problems. Yang further advanced the field with "Multi-robot Cooperative Task Processing in Great Environment" (2008, 5 citations), which integrated task allocation with robot self-localization in large-scale settings, bridging the gap between theoretical coordination and practical deployment. By combining bio-inspired algorithms with real-world constraints, Yang’s work has influenced subsequent studies in distributed robotics and autonomous systems. Their research continues to inspire new generations of engineers seeking to scale multi-robot teams for applications ranging from warehouse logistics to search-and-rescue missions.

Research Focus

Key Achievements

2
H-Index
2
Papers
19
Total Citations
10
Avg Citations/Paper
🏆 Most Cited Paper
Optimal ant colony algorithm based multi-robot task allocation and processing sequence scheduling
14 citations · 2008
📈 Most Prolific Year: 2008 (2 Papers)
🤝 Key Collaborators: 3
🏛 Institutions: Chongqing University of Posts and Telecommunications, Chongqing University

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 15 days ago