Papers
14
Total Citations
294
H-Index
6
About
Baofu Fang is a robotics researcher whose work spans autonomous navigation, simultaneous localization and mapping (SLAM), and affective multi-robot systems. His most influential contribution, "Visual SLAM for Robot Navigation in Healthcare Facility" (2021, 120 citations), demonstrates his ability to bridge foundational robotics techniques with real-world applications, particularly in assistive and healthcare environments. Building on this, his work on point-line fusion SLAM addresses persistent challenges in low-texture scenes, advancing localization accuracy in complex environments. Fang has also made significant strides in autonomous robotic exploration, with his frontier point optimization and multistep path planning approach (2019, 55 citations) offering a practical strategy for improving exploration efficiency in unknown environments. A distinctive thread throughout his research is the integration of emotional and personality models into multi-robot coordination — a relatively novel direction he has pursued since 2013, exploring how affective factors can govern task allocation and coalition formation in robot teams. His collaborative healthcare robot work (2018, 34 citations) reflects the applied ambitions of this line of inquiry. Collectively, Fang's research portfolio, totaling over 280 citations, positions him as a thoughtful contributor to intelligent, socially aware robotic systems.
Research Focus
Key Achievements
Top Papers
- 1Visual SLAM for robot navigation in healthcare facility120 citations · 2021
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- 4Personality driven task allocation for emotional robot team25 citations · 2017
- 5A visual SLAM method based on point-line fusion in weak-matching scene19 citations · 2020
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- 9Task Allocation for Affective Robots Based on Willingness3 citations · 2021
- 10Human Detection Algorithm Based on Edge Symmetry3 citations · 2015