Chengpeng Wang

Shandong Institute of Automation, Chinese Academy of Sciences

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About

Chengpeng Wang is a leading researcher in robotics and autonomous navigation, with a primary focus on 3D LiDAR-based simultaneous localization and mapping (SLAM) and odometry. His work addresses the fundamental challenge of enabling mobile robots to perceive and navigate complex environments with high precision and reliability. Wang’s major contributions include the development of novel sparse geometric frameworks that significantly improve the efficiency and accuracy of 3D LiDAR SLAM. His 2020 paper, "A Novel 3D LiDAR SLAM Based on Directed Geometry Point and Sparse Frame," has garnered 27 citations for its innovative approach to scan-to-map matching, overcoming limitations of traditional methods. Complementing this, his work on "A Novel Sparse Geometric 3-D LiDAR Odometry Approach" (15 citations) introduced a robust odometry solution that leverages accurate depth information and resilience to changing illumination conditions. Together, these contributions have advanced the state of the art in robot localization, directly impacting the development of autonomous systems in both single-robot and multi-robot scenarios. Wang’s research is essential reading for engineers and researchers seeking practical, high-performance solutions for real-world navigation challenges.