Papers
15
Total Citations
630
H-Index
9
About
Yang Cong is a leading researcher in robotic perception and manipulation, with a focus on bridging the gap between human-like sensing and autonomous robot control. His key research areas span 3D vision-based robot manipulation, visual-tactile fusion learning, and underwater robot sensing. Cong’s most impactful contribution is a learning framework for adaptive manipulative skills from human to robot (174 citations), which enables robots to generalize complex, multi-step tasks from demonstrations—a critical advance for industrial and service robotics. He has also authored a comprehensive survey on underwater robot sensing technology (159 citations), highlighting breakthroughs in autonomous manipulation for marine exploration. His work on 3D vision-based manipulation (61 citations) and texture-less object recognition for intelligent manufacturing (48 citations) has advanced real-time, robust pose estimation in cluttered environments. Notably, Cong has pioneered lifelong visual-tactile perception learning, enabling robots to continuously improve object recognition through fused sensory data. His recent work marrying NeRF with feature matching for one-step pose estimation (2024) pushes the boundaries of efficient, CAD-free object localization. With over 600 citations across his top papers, Cong’s research is shaping the future of adaptive, sensor-rich robotic systems.
Research Focus
Key Achievements
Top Papers
- 1A Learning Framework of Adaptive Manipulative Skills From Human to Robot174 citations · 2018
- 2Underwater robot sensing technology: A survey159 citations · 2021
- 3A Comprehensive Study of 3-D Vision-Based Robot Manipulation61 citations · 2021
- 4
- 5Partial Visual-Tactile Fused Learning for Robotic Object Recognition40 citations · 2021
- 6Efficient 3D object recognition via geometric information preservation37 citations · 2019
- 7Lifelong robotic visual-tactile perception learning34 citations · 2021
- 8Robot Tactile Sensing: Vision Based Tactile Sensor for Force Perception28 citations · 2018
- 9Lifelong Visual-Tactile Spectral Clustering for Robotic Object Perception18 citations · 2022
- 10Marrying NeRF with Feature Matching for One-step Pose Estimation7 citations · 2024