Peng Mei

Papers

Total Citations

H-Index

About

Peng Mei is a leading researcher in networked state estimation and mobile robotics, with a focus on resilient communication and control under constrained channels. Her most-cited work, "Encoding–Decoding-Based Recursive State Estimation for Mobile Robot Localization: A Multiple Description Case" (2025, 6 citations), introduces a novel two-description coding scheme that optimizes channel resource utilization for recursive state estimation in mobile robot localization. This contribution addresses a critical challenge in autonomous systems: maintaining accurate positioning when data transmission is unreliable or bandwidth-limited. By developing encoding-decoding strategies that preserve estimation fidelity despite packet loss or delays, Mei has advanced the practical deployment of robots in real-world environments where communication is imperfect. Her research bridges information theory and control systems, offering robust solutions for multi-sensor fusion and distributed estimation. With growing recognition for her work, Mei continues to shape the future of intelligent, communication-aware robotics—making her a key figure for students and researchers interested in the intersection of estimation theory, networked control, and mobile autonomy.