Xiaofeng Zheng

Chongqing University of Posts and Telecommunications

Papers

Total Citations

H-Index

About

Xiaofeng Zheng is a researcher in robotics and autonomous systems, with a primary focus on simultaneous localization and mapping (SLAM) for mobile robots. His key contributions lie in advancing filtering techniques for SLAM, particularly through the development of improved Rao-Blackwellized H∞ filters, which enhance robustness and accuracy in uncertain environments. This work, detailed in his most-cited paper from 2016, has garnered 5 citations, reflecting its foundational role in addressing challenges in robot navigation. Zheng’s research integrates probabilistic methods and control theory to optimize state estimation, enabling more reliable autonomous operation. His achievements include refining SLAM algorithms to reduce computational complexity while maintaining performance, a critical step for real-time applications. By pushing the boundaries of filter-based SLAM, Zheng contributes to the broader field of mobile robotics, supporting advancements in autonomous vehicles, exploration, and service robots. His work is particularly valuable for students and researchers seeking practical solutions to localization and mapping problems in dynamic, noisy environments.