Papers
5
Total Citations
196
H-Index
4
About
Zhijiang Shao is a leading researcher in motion planning and optimization for autonomous robotic systems, with a focus on nonholonomic and multi-robot coordination. His work addresses fundamental challenges in trajectory planning for car-like robots operating in constrained, narrow environments. Shao’s most influential contribution is the development of *simultaneous dynamic optimization*, a trajectory planning method for nonholonomic car-like robots (76 citations), which has become a cornerstone for efficient motion in tight spaces. He further advanced the field with *optimal cooperative maneuver planning* for multiple nonholonomic robots in tiny environments (65 citations), introducing adaptive-scaling constrained optimization to solve the time-optimal Multi-Vehicle Trajectory Planning problem under static obstacles. His *spatio-temporal decomposition* strategy (42 citations) provides a knowledge-based initialization for parallel parking optimization, enhancing real-world applicability. Shao has also explored balance recovery for biped robots under disturbance, analyzing feet-ground constraints. With over 196 citations across his top works, Shao’s research is essential for students and engineers tackling autonomous navigation, multi-robot coordination, and constrained optimization in robotics.
Research Focus
Key Achievements
Top Papers
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