Guangkun Tang
Papers
1
Total Citations
2
H-Index
1
About
Guangkun Tang is a researcher in robotics and autonomous systems, with a primary focus on cooperative multi-agent coordination and intelligent task planning. His most-cited work, "Cooperative Task Assignment and Path Planning via an A*-Market-Based Algorithm" (2022), introduces a novel hybrid approach that integrates A* search with market-based mechanisms to solve complex, real-time assignment and navigation problems for teams of robots or drones. This contribution addresses a critical challenge in swarm robotics: balancing optimal task allocation with efficient, collision-free path planning. Although his citation count is still emerging, with 2 citations for this paper, the work demonstrates a strong foundation in algorithmic design and practical applicability, likely influencing further studies in distributed decision-making and autonomous logistics. Tang’s research sits at the intersection of operations research and artificial intelligence, offering scalable solutions for dynamic environments. His achievements include advancing the efficiency of multi-robot systems, which has potential applications in disaster response, warehouse automation, and exploration. For students and researchers, Tang’s work exemplifies how classical algorithms can be adapted for modern, decentralized coordination problems.
Research Focus
Key Achievements
Top Papers
- 1