Yunping Liu

Nanjing University of Information Science and Technology

Papers

Total Citations

H-Index

About

Yunping Liu is a robotics and computer vision researcher whose work focuses on autonomous systems for underwater and complex environments. Her key research areas include object detection for marine robotics, robotic grasp detection, and mobile robot design. Liu’s most cited paper, “A Marine Object Detection Algorithm Based on SSD and Feature Enhancement” (2020, 49 citations), addresses the challenge of autonomous sea urchin detection for underwater robots, enhancing the Single-Shot MultiBox Detector (SSD) to improve accuracy in aquatic settings. This work has significant implications for sustainable aquaculture and automated fishing. More recently, in “DSNet: Double Strand Robotic Grasp Detection Network Based on Cross Attention” (2024, 18 citations), she introduced a novel architecture combining transformer and U-Net branches to reconcile local and global feature extraction for robotic grasping, advancing manipulation in unstructured environments. Liu also contributed to mobile robotics with her design of a wheel-tracked moving system (WTMS) for exploration robots (2016), demonstrating her versatility from hardware to algorithms. Her research, though early in citation impact, shows promise in bridging perception and action for autonomous systems, particularly in marine and field robotics.