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
Top Papers
- 1Research on map merging for multi-robotic system based on RTM25 citations · 2012
- 2Range scan matching and Particle Filter based mobile robot SLAM16 citations · 2010
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- 7LRF-based data processing algorithm for map building of mobile robot12 citations · 2010
- 8Automatic Docking and Charging of Mobile Robot Based on Laser Measurement11 citations · 2021
- 9Robustness improvement of human detecting and tracking for mobile robot10 citations · 2012
- 10Multimodal Human-robot Interaction on Service Robot9 citations · 2021