Papers

2

Total Citations

12

H-Index

2

About

Xingnan Liang is a robotics researcher specializing in assistive mobility systems, with a focus on intelligent wheelchair and bed docking technologies. Their key research areas include computer vision, sensor fusion, and autonomous control for healthcare robotics. Liang's major contributions center on developing robust docking control methods that combine artificial landmark identification with ultrasound sensors, enabling precise autonomous alignment between wheelchairs and beds. Their 2017 paper on vision-ultrasound fusion docking has garnered 7 citations, while their 2018 work on position-based visual servo control for Mecanum-wheeled omnidirectional systems has received 5 citations. These studies address critical challenges in indoor assistive robotics, particularly for elderly and disabled users requiring seamless transfer between mobility devices. Liang's work demonstrates practical applications of visual servoing and sensor integration to enhance independence and safety in healthcare environments. Their research represents an important step toward fully autonomous patient transfer systems, with potential to reduce caregiver burden and improve quality of life for individuals with limited mobility.

Research Focus

Key Achievements

2
H-Index
2
Papers
12
Total Citations
6
Avg Citations/Paper
🏆 Most Cited Paper
Wheelchair/bed docking control based on the combination of vision and ultrasound
7 citations · 2017
📈 Most Prolific Year: 2017 (1 Papers)
🤝 Key Collaborators: 4
🏛 Institutions: Beijing University of Technology, Beijing Academy of Artificial Intelligence

Top Papers

  1. 1
  2. 2

Key Collaborators

Contact & Links

Available for collaboration
Content generated · 13 days ago