Tangyike Zhang
Papers
2
Total Citations
4
H-Index
2
About
Tangyike Zhang is a robotics researcher specializing in autonomous navigation for complex, unstructured, and crowded environments. His work bridges the gap between theoretical motion planning and real-world deployment, with a focus on safety and adaptability. Zhang’s key contributions include developing a robot crowd navigation framework using spatio-temporal interaction graphs and danger zones, which addresses the critical challenge of safe movement in partially observable, human-dense spaces—a step beyond traditional simulation-based approaches. He also advanced all-terrain vehicle (ATV) autonomy for urban search and rescue, tackling navigation on stairs and other challenging terrain where L5 self-driving remains impractical. Though early in his career, his papers have each garnered 2 citations, reflecting foundational work that is gaining traction. Zhang’s research is notable for its practical orientation: by targeting real-world constraints like partial observability and unstructured environments, he is helping to make robotic systems more resilient and deployable in emergency scenarios. His work stands as a promising contribution to the fields of mobile robotics, human-robot interaction, and field robotics.
Research Focus
Key Achievements
Top Papers
- 1
- 2ATV Navigation in Complex and Unstructured Environment Containing Stairs2 citations · 2020