Chaowei Ma

Papers

Total Citations

206

H-Index

About

Chaowei Ma is a computer vision and robotics researcher whose work centers on Simultaneous Localization and Mapping (SLAM), with a particular focus on enabling robust performance in dynamic, real-world environments. Recognizing that traditional SLAM systems are constrained by an oversimplified static world assumption, Ma has dedicated his research to developing semantically-aware and depth-informed solutions that dramatically improve localization and mapping accuracy when moving objects are present. His most influential contribution, SOF-SLAM: A Semantic Visual SLAM for Dynamic Environments (2019), has garnered 159 citations, establishing him as a notable voice in the field. Building on this foundation, he introduced SDF-SLAM (2020), a semantic depth filter approach that further refines accuracy in challenging dynamic scenes, earning an additional 42 citations. Ma has also explored hybrid methodologies, as demonstrated in Direct-ORB-SLAM, which integrates direct and feature-based techniques to advance monocular mapping capabilities. Collectively, his research addresses one of the most pressing practical challenges in autonomous navigation and robotics — bridging the gap between controlled laboratory conditions and the complexity of real-world deployment — making his work highly relevant for students and engineers developing next-generation autonomous systems.