Yajun Liao
Papers
1
Total Citations
2
H-Index
1
About
Yajun Liao is a robotics researcher whose work lies at the intersection of human-robot interaction, real-time motion planning, and safety-critical control. Liao’s most cited paper, “Real-time safe motion generation through dynamical system modulation with multiple depth sensors” (2017), tackles a fundamental challenge for collaborative robots: how to move safely and adaptively in dynamic, human-filled environments. The proposed approach uses multiple depth sensors to modulate dynamical systems in real time, allowing robots to react instantly to obstacles without pre-planned paths. This work has garnered 2 citations and represents a key step toward making robots viable partners in daily life and production settings. Liao’s contributions are particularly notable for bridging theoretical control methods with practical sensor integration, addressing the pressing need for robots that can operate safely alongside humans without sacrificing efficiency. By focusing on real-time adaptability, Liao’s research helps pave the way for the next generation of autonomous systems that are both responsive and trustworthy—a critical requirement as robots move from factory floors into homes and public spaces.
Research Focus
Key Achievements
Top Papers
- 1