Hongpeng Wang

Shenzhen Institute of Information Technology, Harbin Institute of Technology, Nankai University

Papers

Total Citations

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About

Hongpeng Wang is a researcher whose work spans robotics, computer vision, and autonomous systems, with contributions ranging from multi-robot coordination to medical robotics and human-robot interaction. His most recognized contribution, the Distance- and Velocity-Based Simultaneous Obstacle Avoidance and Target Tracking (DV-SOATT) method, addresses the complex challenge of enabling multiple wheeled mobile robots to navigate shared workspaces safely and efficiently — a problem central to modern robotics deployment. Published in 2023, this work has already accumulated 17 citations, reflecting its relevance to the rapidly growing field of autonomous mobile systems. Earlier in his career, Wang demonstrated breadth by tackling human-robot interaction challenges, developing a real-time hand gesture recognition algorithm tailored for embedded systems — a practically motivated contribution to intelligent robot design. More recently, his research has ventured into medical robotics, where he proposed a depth-awareness shared self-supervised approach for bronchial orifice segmentation to aid vision-based robotic bronchoscopy, addressing the significant challenge of labeling inconsistencies in complex anatomical structures. Together, Wang's body of work reflects a consistent drive to solve real-world robotic challenges across diverse and impactful application domains.