Papers
5
Total Citations
105
H-Index
3
About
Zhiqiang Jian is a leading researcher in autonomous mobile robotics, with a primary focus on path planning and navigation in complex, dynamic environments. His work bridges the gap between global route optimization and real-time local control, most notably through the "Global-Local Coupling Two-Stage Path Planning" (CTSP) method, which has garnered 78 citations for its novel approach to solving nonlinear optimization challenges in robot motion. Jian has also advanced kinodynamic local planning with the Long-Term Dynamic Window Approach, enabling differential wheeled robots to navigate safely in both static and crowded settings. His contributions extend to parametric path optimization for improved smoothness and collision avoidance, as well as multi-risk aware trajectory planning for car-like robots operating in highly dynamic environments. More recently, he introduced the DVT-Tree, a dynamic visible topology tree that facilitates efficient mapless navigation in maze-like unknown spaces. With a growing citation impact and a portfolio of innovative algorithms published in top venues from 2021 to 2023, Jian is shaping the future of autonomous navigation by making robots smarter, safer, and more adaptable in real-world conditions.
Research Focus
Key Achievements
Top Papers
- 1A Global-Local Coupling Two-Stage Path Planning Method for Mobile Robots78 citations · 2021
- 2
- 3Parametric Path Optimization for Wheeled Robots Navigation4 citations · 2022
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- 5