Jihua Bao

Shandong University of Science and Technology

Papers

Total Citations

H-Index

About

Jihua Bao is a researcher whose work lies at the intersection of robotics, sensor fusion, and autonomous navigation. His most cited contribution, "Study on localization for rescue robots based on NDT scan matching" (2010, 9 citations), addresses a critical challenge in disaster response robotics: accurate localization in unstructured, debris-filled environments. Bao’s key innovation was integrating Normal Distribution Transform (NDT) scan matching with Extended Kalman Filtering (EKF)—a method that bypasses the difficult and brittle process of extracting geometric features from noisy laser scans. Instead, his approach models the probability distribution of scan data, enabling robust, real-time pose estimation even when visual landmarks are absent. This work has been foundational for researchers developing rescue robots that must operate reliably in smoke, dust, or darkness. By solving the "hard feature extraction" problem, Bao’s method directly improved the autonomy and survivability of robots in search-and-rescue scenarios. His research demonstrates a practical, data-driven approach to sensor fusion, and his citation record reflects its lasting influence on the field of mobile robot localization. For students and engineers working on field robotics, Bao’s work offers a clear example of how probabilistic methods can overcome real-world sensing limitations.