Ziqi Pei
Papers
1
Total Citations
4
H-Index
1
About
Ziqi Pei is a researcher in robotics and autonomous systems, with a primary focus on simultaneous localization and mapping (SLAM) in dynamic and occluded environments. Their most-cited work, "Dynamic simultaneous localization and mapping based on object tracking in occluded environment" (2024), addresses a critical challenge in mobile robotics: enabling resource-constrained embedded devices to perform robust SLAM despite visual occlusions and limited processing power. By integrating object tracking into the SLAM pipeline, Pei’s approach improves pose estimation accuracy and map consistency in real-world scenarios where traditional algorithms fail. This contribution is especially relevant for applications in warehouse automation, search-and-rescue, and autonomous navigation in cluttered spaces. With 4 citations already, the work is gaining traction among researchers tackling low-power, high-performance robotics. Pei’s research bridges the gap between theoretical SLAM advances and practical deployment on embedded systems, making autonomous robots more reliable in challenging, dynamic settings. Their work exemplifies how targeted algorithmic innovation can overcome hardware limitations, paving the way for more capable and accessible robotic platforms.
Research Focus
Key Achievements
Top Papers
- 1