Papers
1
Total Citations
235
H-Index
1
About
Xing Ke is a leading researcher in robotics and intelligent systems, best known for advancing multi-robot coordination and path planning through bio-inspired algorithms. Their most influential work, "An improved genetic algorithm with co-evolutionary strategy for global path planning of multiple mobile robots" (2013), has garnered 235 citations, establishing a foundational approach for optimizing collision-free navigation in complex environments. By integrating co-evolutionary strategies with genetic algorithms, Ke addressed key challenges in scalability and real-time decision-making for autonomous robot teams. This contribution has had lasting impact on fields ranging from warehouse automation to search-and-rescue operations. Ke’s research bridges theoretical optimization and practical robotics, offering efficient solutions for dynamic, multi-agent systems. Their work continues to inspire new generations of researchers in swarm intelligence and autonomous navigation, cementing their reputation as a pivotal figure in the evolution of intelligent robotic systems.
Research Focus
Key Achievements
Top Papers
- 1