Papers
26
Total Citations
824
H-Index
12
About
Shihan Kong is a robotics researcher whose work sits at the dynamic intersection of aquatic robotics, computer vision, and intelligent control systems. His research focuses primarily on developing autonomous robotic solutions for underwater and water-surface environments, with a particular emphasis on environmental applications such as marine garbage collection and biological specimen retrieval. Kong's most influential contribution—a soft manipulator for underwater grasping (224 citations)—demonstrated how compliant robotic designs could safely and effectively operate in shallow marine environments, offering a compelling alternative to human divers. Complementing this hardware-focused work, his 2019 GAN-based method for real-time underwater visual enhancement (141 citations) addressed one of the field's most persistent challenges: poor image quality that hampers robotic perception. His development of intelligent water surface cleaning robots, supported by multiple modified YOLO-based detection algorithms, has further established him as a leading voice in vision-guided aquatic environmental robotics, collectively drawing over 200 additional citations. Beyond cleaning applications, Kong has explored miniature robotic fish with novel magnetic actuation, underwater binocular vision systems, and reinforcement learning-driven manipulation, revealing a broad and forward-thinking research agenda. His cumulative body of work reflects a commitment to bridging cutting-edge robotics with pressing real-world environmental challenges.
Research Focus
Key Achievements
Top Papers
- 1
- 2Towards Real-Time Advancement of Underwater Visual Quality With GAN141 citations · 2019
- 3
- 4
- 5
- 6
- 7
- 8
- 9Pruning-Based YOLOv4 Algorithm for Underwater Gabage Detection15 citations · 2021
- 10