AI-Enhanced Soft Robotic Endoscopy System for Precision Colonoscopy and Real-Time 3D Navigation Gastrointestinal (GI) cancers, including colorectal and stomach cancers, remain among the leading causes of cancer-related deaths worldwide. Early detection through colonoscopy significantly improves survival, yet conventional endoscopic systems are rigid, operator-dependent, and carry a risk of patient discomfort  and tissue trauma. This project addresses these limitations by developing an AI-Enhanced Soft Robotic Endoscopy System that combines AI-driven design automation and Simultaneous Localization and Mapping (SLAM)-based navigation to improve safety, flexibility, and diagnostic accuracy during colonoscopy procedures.

The innovation question guiding this research is: How can artificial intelligence and real-time 3D mapping be integrated into a soft robotic platform to enable safer, autonomous, and more precise endoscopic navigation in complex gastrointestinal environments? The project seeks to advance robotic flexibility, adaptive navigation, and intelligent control through the convergence of soft continuum robotics, foundation models for automated design, and visual–inertial SLAM algorithms. With the growing global burden of GI cancers, there is an urgent need for next-generation endoscopic tools that reduce procedural complexity while improving early-stage lesion detection.

Technologically, it will advance AI-driven medical robotics and autonomous navigation, while economically, it will open opportunities for innovation and commercialization in intelligent medical devices. 

The project’s Impact Plan emphasizes translational potential through collaboration between clinicians, engineers, and industry partners, bridging research excellence with societal benefit and contributing to the digital transformation of healthcare.