Wenying Wu

Papers

Total Citations

H-Index

About

Wenying Wu is a leading researcher in multi-robot systems, with a primary focus on decentralized path planning and collision avoidance. Her most impactful work introduces a novel prioritization scheme for multi-robot path deconfliction, where robots plan their paths sequentially based on "path prospects"—a metric that evaluates the complexity and feasibility of each robot's intended trajectory. This approach significantly improves computational tractability over centralized methods, enabling scalable coordination in cluttered environments. Her 2020 paper on this topic has garnered 57 citations, underscoring its influence in the field of robotics and autonomous systems. Wu's contributions are particularly notable for addressing the scalability bottleneck in multi-robot coordination, offering a practical solution that balances efficiency with safety. Her work is widely referenced in research on warehouse automation, drone swarms, and autonomous vehicle coordination. By advancing decoupled planning algorithms, Wu has helped pave the way for more robust and scalable multi-robot systems, making her a key figure in modern robotics research.