Pengling Wang
Papers
1
Total Citations
4
H-Index
1
About
Pengling Wang is a researcher whose work centers on mobile robot navigation and sensor fusion, with a particular focus on simultaneous localization and mapping (SLAM) in indoor environments. Their most cited contribution, a 2008 study on a SLAM algorithm integrating CCD image data with odometer readings, addresses the critical challenge of enabling robots to navigate and build maps of unknown spaces autonomously. By combining visual and wheel-encoder information, Wang proposed a practical solution for robust localization without relying on expensive or external positioning systems. Though this foundational work has garnered 4 citations to date, it represents an early effort in a field that has since grown explosively. Wang’s research speaks to the enduring problem of sensor integration in robotics, and their approach continues to inform studies on low-cost, vision-based navigation. For students and researchers exploring SLAM or indoor robot autonomy, Wang’s work offers a clear, grounded example of how combining complementary sensors can overcome the limitations of individual systems in real-world applications.
Research Focus
Key Achievements
Top Papers
- 1