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Int J Comput Assist Radiol Surg. 2010 Jul;5(4):317-25. doi: 10.1007/s11548-010-0481-0. Epub 2010 May 18.

Development of a colon endoscope robot that adjusts its locomotion through the use of reinforcement learning.

Author information

1
Waseda University, Tokyo, Japan. gabrit20@yahoo.it

Abstract

PURPOSE:

Fibre optic colonoscopy is usually performed with manual introduction and advancement of the endoscope, but there is potential for a robot capable of locomoting autonomously from the rectum to the caecum. A prototype robot was designed and tested.

METHODS:

The robot colonic endoscope consists in a front body with clockwise helical fin and a rear body with anticlockwise one, both connected via a DC motor. Input voltage is adjusted automatically by the robot, through the use of reinforcement learning, determining speed and direction (forward or backward).

RESULTS:

Experiments were performed both in-vitro and in-vivo, showing the feasibility of the robot. The device is capable of moving in a slippery environment, and reinforcement learning algorithms such as Q-learning and SARSA can obtain better results than simply applying full tension to the robot.

CONCLUSIONS:

This self-propelled robotic endoscope has potential as an alternative to current fibre optic colonoscopy examination methods, especially with the addition of new sensors under development.

PMID:
20480247
DOI:
10.1007/s11548-010-0481-0
[Indexed for MEDLINE]

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