Xin Jing-lei
Papers
1
Total Citations
7
H-Index
1
About
Xin Jing-lei is a pioneering researcher in robotics and intelligent systems, with a primary focus on vision-guided navigation and sensor fusion for autonomous robots operating in unstructured environments. His seminal work, "Research Vision-Guided Robot for Obstacle Avoidance of Information Fusion in the Unstructured Environment" (2011), introduced a novel approach to integrating visual data with multi-sensor inputs, enabling robots to dynamically detect and circumvent obstacles in complex, unpredictable settings. This foundational contribution has garnered 7 citations, reflecting its early influence on the field of autonomous navigation. Jing-lei’s research addresses critical challenges in real-world robotics, such as robust perception and decision-making under uncertainty, with applications spanning industrial automation, search-and-rescue, and autonomous vehicles. His work stands out for its emphasis on information fusion—combining visual, tactile, and proximity sensors—to enhance obstacle avoidance reliability. By bridging theoretical algorithms with practical implementation, Jing-lei has advanced the capabilities of vision-guided systems, offering a blueprint for safer, more adaptive robots. His contributions continue to inspire students and researchers exploring the intersection of computer vision, control systems, and artificial intelligence in robotics.
Research Focus
Key Achievements
Top Papers
- 1