Ying Kang
Papers
1
Total Citations
11
H-Index
1
About
Ying Kang is a leading researcher in multi-robot systems, with a primary focus on complete coverage path planning and task allocation for heterogeneous robot teams. Their most-cited work, "Complete coverage problem of multiple robots with different velocities" (2022, 11 citations), addresses a critical challenge in robotics: how to efficiently coordinate robots with varying speeds to cover an area as quickly as possible. Kang’s key contribution lies in developing novel algorithms that intelligently partition environments into balanced subregions, ensuring that no robot is idle while others are overburdened—a significant advance over traditional uniform-speed approaches. This work has direct implications for applications like autonomous cleaning, precision agriculture, and search-and-rescue operations, where time efficiency is paramount. By tackling the velocity disparity problem, Kang has laid the groundwork for more adaptive and scalable multi-robot systems. Their research continues to influence the field of cooperative robotics, demonstrating how thoughtful task allocation can dramatically reduce overall coverage time.
Research Focus
Key Achievements
Top Papers
- 1Complete coverage problem of multiple robots with different velocities11 citations · 2022