Zheng Xiangmei

Papers

Total Citations

H-Index

About

Zheng Xiangmei is a robotics researcher whose work focuses on autonomous navigation and spatial perception for mobile robots. Her key contributions lie in developing algorithms for place recognition and orientation estimation, which are critical for enabling robots to operate reliably in indoor environments. In her 2016 paper, "Sonar-based place recognition using joint sparse coding method," she addressed the fundamental challenge of a robot recognizing previously visited locations—a core problem in simultaneous localization and mapping (SLAM). By framing place recognition as a classification task and applying joint sparse coding to sonar data, she introduced a novel approach that improved robustness in low-visibility conditions. Her 2018 work, "Orientation estimate of indoor mobile robot using laser scans," further advanced robot self-localization by refining heading estimation from 2D laser data. Though her citation counts are modest—4 and 2 respectively—these papers represent foundational steps in sensor-based navigation, particularly for resource-constrained platforms. Zheng’s research demonstrates a methodical focus on practical, sensor-driven solutions for indoor robotics, contributing to the broader goal of creating perceptually aware autonomous systems.