Tianjun Liao
Papers
1
Total Citations
7
H-Index
1
About
Tianjun Liao is a robotics researcher whose work focuses on integrating formal methods, motion planning, and control to ensure safety and reliability in autonomous systems operating under uncertainty. His primary research areas include hierarchical motion planning, probabilistic temporal logic, and safe-return constraints for robotic missions. Liao’s major contribution lies in developing frameworks that allow robots to satisfy complex, time-sensitive tasks while guaranteeing they can safely return to a designated state—a critical capability for real-world deployment in dynamic or hazardous environments. His most-cited paper, "Hierarchical Motion Planning Under Probabilistic Temporal Tasks and Safe-Return Constraints" (2023, 7 citations), introduces a novel approach that goes beyond simple collision avoidance to address more general safety requirements. This work is notable for bridging the gap between high-level task specifications and low-level control, enabling robots to reason about both mission objectives and risk. With growing interest in verifiable autonomy, Liao’s research is poised to influence the next generation of resilient robotic systems, particularly in applications like search-and-rescue, autonomous exploration, and human-robot collaboration.
Research Focus
Key Achievements
Top Papers
- 1