Chenjie Wang

Papers

Total Citations

127

H-Index

About

Chenjie Wang is a leading researcher in robotics and autonomous systems, with a primary focus on Simultaneous Localization and Mapping (SLAM) for dynamic and complex environments. His most influential work, "DV-LOAM: Direct Visual LiDAR Odometry and Mapping" (2021, 66 citations), introduces a groundbreaking fusion framework that integrates direct visual and LiDAR data for robust SLAM in self-driving cars, addressing critical challenges in real-time perception and mapping. Wang has also pioneered the application of intelligent robotics in critical infrastructure, as demonstrated in "An intelligent robot for indoor substation inspection" (2020, 56 citations), which enhances safety and efficiency in power supply maintenance. His research extends to aerial-ground robot collaboration, as seen in "The collaborative mapping and navigation based on visual SLAM in UAV platform" (2020), and dynamic scene reconstruction with "DymSLAM: 4D Dynamic Scene Reconstruction Based on Geometrical Motion Segmentation" (2020). Wang’s contributions are widely cited, reflecting their impact on advancing SLAM technology for both static and dynamic environments, with notable achievements in bridging theoretical innovation and practical deployment in industrial and autonomous systems.