Shukang Chen
Papers
2
Total Citations
15
H-Index
2
About
Shukang Chen is a rising researcher in the field of robotics, with a primary focus on safety-critical control and redundant manipulator motion planning. His work addresses fundamental challenges in ensuring both performance and safety in autonomous robotic systems. Chen’s most notable contribution is a novel safety-critical trajectory tracking method for mobile robots, which leverages control barrier functions (CBFs) to guarantee collision avoidance and performance bounds simultaneously. This work, published in 2024, has already garnered 11 citations, signaling its immediate impact on the safe navigation community. In parallel, Chen has made significant strides in the control of redundant robot manipulators. He proposed and validated a new acceleration-level repetitive motion planning (RMP) scheme, a critical advancement over traditional velocity-level approaches, enabling smoother and more precise joint motion for industrial applications. This 2023 study, with 4 citations, provides a rigorous framework for improving the efficiency and accuracy of manipulators in repetitive tasks. Chen’s research bridges theoretical control guarantees with practical robotic implementation, positioning him as a promising contributor to the next generation of safe and dexterous autonomous systems.
Research Focus
Key Achievements
Top Papers
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- 2