Papers

45

Total Citations

300

H-Index

9

About

Xiuzhi Li is a robotics researcher whose work centers on autonomous mobile robotics, simultaneous localization and mapping (SLAM), and human-robot interaction. Over more than a decade of contributions, Li has made significant strides in enabling robots to navigate and understand complex environments through innovative algorithmic approaches. His foundational work on laser scan-matching and Rao-Blackwellized Particle Filter-based SLAM (2010, 16 citations) established effective indoor navigation frameworks, while subsequent research extended these capabilities to monocular camera-based SLAM (2016, 16 citations) and robust 3D map building using an improved RANSAC algorithm incorporating DS evidence theory (2016, 15 citations). Li's multi-robot research, particularly his RTM-based map merging method employing SIFT feature matching (2012, 25 citations), represents his most widely recognized contribution, addressing the challenges of large-scale collaborative exploration. Beyond navigation, he has tackled practical deployment challenges, including autonomous robot docking and charging via lidar (2021, 11 citations), obstacle avoidance for intelligent wheelchair beds (2017, 13 citations), and multimodal human-robot interaction (2021, 9 citations). Li's body of work reflects a consistent commitment to bridging theoretical robotics research with real-world assistive and service robot applications.

Research Focus

Key Achievements

9
H-Index
45
Papers
300
Total Citations
7
Avg Citations/Paper
🏆 Most Cited Paper
Research on map merging for multi-robotic system based on RTM
25 citations · 2012
📈 Most Prolific Year: 2012 (8 Papers)
🤝 Key Collaborators: 61
🏛 Institutions: Beijing University of Technology, Beijing Academy of Artificial Intelligence, Beihang University

Top Papers

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Key Collaborators

Contact & Links

Available for collaboration
Content generated · 14 days ago