Colorectal cancer is one of the most commonly diagnosed cancers worldwide and a leading cause of cancer-related deaths, making effective screening and early detection essential. Colonoscopy is considered the gold standard for this purpose, as it allows direct visual inspection of the colon. However, the procedure is highly dependent on the operator’s skill due to the complex and deformable anatomy of the colon. This can lead to inconsistent examination quality, missed lesions, and, in rare cases, complications.
The challenges have motivated research into robotic and intelligent assistance systems that can improve navigation, precision, and reliability during colonoscopy. In particular, vision-based control seems like a promising approach, as the procedure heavily relies on visual feedback from the integrated camera.
This assignment is formulated within this context, aiming to contribute to the development of more autonomous endoscopic systems, making the procedure more reliable and safer.