Wun-Fang Li
Papers
2
Total Citations
18
H-Index
2
About
Wun-Fang Li’s research centers on assistive robotics, human-robot interaction, and autonomous navigation, with a particular focus on enhancing mobility for individuals with disabilities. His most influential work, “RGB-D sensor based SLAM and human tracking with Bayesian framework for wheelchair robots” (2013, 13 citations), introduced a novel approach combining visual simultaneous localization and mapping (SLAM) with human tracking using a Microsoft Kinect sensor. By integrating speeded-up robust feature (SURF) algorithms with a Bayesian framework, Li enabled wheelchair robots to autonomously map environments and follow a user, significantly improving safety and independence in dynamic settings. In his related study, “Accompanist detection and following for wheelchair robots with fuzzy controller” (2012, 5 citations), he advanced multisensory data fusion—merging laser range finder data with other inputs—to reliably detect and track a companion, demonstrating practical human-robot coordination. These contributions underscore Li’s impact on developing intuitive, real-world assistive technologies, laying groundwork for smarter, more responsive mobility aids. His work remains a touchstone for researchers exploring sensor fusion and adaptive control in service robotics.
Research Focus
Key Achievements
Top Papers
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