Rencai Jin
Papers
1
Total Citations
2
H-Index
1
About
Rencai Jin is a researcher whose work centers on advancing autonomous navigation and perception in robotics, with a particular focus on simultaneous localization and mapping (SLAM) systems. His key contributions lie in improving real-time robot positioning through innovative sensor fusion techniques, as demonstrated in his highly regarded paper "A Real-Time Robot Location Algorithm Based on Improved Point-Line Feature Fusion" (2023). In this work, Jin addresses a critical challenge in dense environments—the over-extraction of line segments that leads to mismatching and reduced system accuracy—by proposing the IPLI-SLAM method. This algorithm enhances visual SLAM by intelligently fusing point and line features, significantly boosting robustness and precision in complex settings. While his citation count is currently modest, the practical implications of his research are substantial, offering a scalable solution for robots operating in cluttered real-world spaces. Jin’s work exemplifies a focused effort to bridge theoretical SLAM frameworks with deployable, high-performance applications, making him a promising contributor to the field of robotics and autonomous systems.
Research Focus
Key Achievements
Top Papers
- 1