Bowen Pan

Massachusetts Institute of Technology, China University of Geosciences

Papers

Total Citations

280

H-Index

About

Bowen Pan is a researcher whose work bridges computer vision and robotics, with a primary focus on enabling machines to perceive and navigate their environments intelligently. His key research areas include semantic segmentation, spatial perception, and humanoid robot motion control. Pan’s most significant contribution is his pioneering work on cross-view semantic segmentation for sensing surroundings, introduced in a 2020 paper that has garnered 277 citations. This novel visual task extracts the spatial configuration of objects and free space from observations, directly enhancing robot perception and autonomous navigation. By addressing how machines can understand their surroundings from multiple perspectives, Pan’s research has practical implications for robotics, autonomous driving, and augmented reality. Earlier in his career, he explored omnidirectional motion control for humanoid soccer robots, demonstrating his long-standing interest in applying perception to dynamic, real-world systems. While his early work on motion control has fewer citations, it laid the groundwork for his later, more impactful contributions. Pan’s research is particularly relevant for students and researchers interested in the intersection of computer vision and robotics, offering insights into how machines can achieve human-like spatial awareness.