Jiazhi Song

Papers

Total Citations

H-Index

About

Jiazhi Song is a robotics researcher whose work focuses on the critical intersection of motion planning, stability, and safety for mobile manipulators and reconfigurable vehicles operating in challenging environments. Their primary research areas include dynamic-stability-constrained trajectory optimization, chance-constrained planning under uncertainty, and rollover prevention for robotic systems. Song’s most notable contribution is a hierarchical framework for online, point-to-point optimal trajectory planning of mobile manipulators on rough terrain, which explicitly enforces zero moment point stability constraints—a foundational paper that has garnered 11 citations since 2022. Building on this, Song developed a chance-constrained method for rollover-free manipulation planning that accounts for uncertain payload mass, addressing a critical safety gap in real-world robotic applications. Their work on computationally efficient chance-constrained motion planning for reconfigurable vehicles with limited terrain accuracy further demonstrates their ability to tackle practical, high-stakes problems. With a growing citation record and a clear focus on robust, stability-aware algorithms, Song is establishing themselves as a key contributor to safe autonomous navigation in unstructured environments.