Pengju Zhang
Papers
2
Total Citations
13
H-Index
2
About
Pengju Zhang is a robotics researcher whose work centers on advancing simultaneous localization and mapping (SLAM) and 3D reconstruction for autonomous systems operating in challenging environments. His key research areas include multi-sensor fusion, semantic SLAM, and underwater robot localization. Zhang’s major contribution is the development of CID-SIMS, a complex indoor dataset with semantic information and multi-sensor data from a ground wheeled robot viewpoint, which has garnered 10 citations since 2023. This dataset addresses critical gaps in leveraging semantic information to enhance SLAM and 3D reconstruction performance for applications like floor sweeping and food delivery robots. In 2024, Zhang introduced an innovative underwater robot self-localization method using tightly coupled events, images, inertial, and acoustic fusion, achieving 3 citations. This work tackles the persistent challenge of error accumulation in dead reckoning methods by integrating multiple sensing modalities. His research is notable for pushing the boundaries of autonomous navigation in both indoor and underwater domains, offering practical solutions for real-world robotic systems. Zhang’s work continues to inspire advancements in robust, multi-sensor perception for autonomous robots.
Research Focus
Key Achievements
Top Papers
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- 2