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Design of Sensor Network for Estimation of the Shape of Flexible Endoscope
Author(s) -
Jae-Woo Lee
Publication year - 2016
Publication title -
journal of the korea academia-industrial cooperation society
Language(s) - English
Resource type - Journals
eISSN - 2288-4688
pISSN - 1975-4701
DOI - 10.5762/kais.2016.17.2.299
Subject(s) - euler angles , control theory (sociology) , butterworth filter , filter (signal processing) , euler's formula , noise (video) , kinematics , computer science , position (finance) , acoustics , low pass filter , computer vision , mathematics , artificial intelligence , physics , high pass filter , geometry , mathematical analysis , control (management) , classical mechanics , finance , economics , image (mathematics)
In this paper, a method of shape prediction of an endoscope handling robot that can imitate a surgeon's behavior using a sensor network is suggested. Unit sensors, which are composed of a 3-axis magnetometer and 3-axis accelerometer pair comprise the network through CAN bus communication. Each unit of the sensor is used to detect the angle of the points in the longitudinal direction of the robot, which is made from a flexible tube. The signals received from the sensor network were filtered using a low pass Butterworth filter. Here, a Butterworth filter was designed for noise removal. Finally, the Euler angles were extracted from the signals, in which the noise was filtered by the low path Butterworth filter. Using this Euler angle, the position of each sensor on the sensor network is estimated. The robot body was assumed to consist of links and joints. The position of each sensor can be assumed to be attached to the center of each link. The position of each link was determined using the Euler angle and kinematics equation. The interpolation was carried out between the positions of the sensors to be able to connect each point smoothly and obtain the final posture of the endoscope in operation. The experimental results showed that the shape of the colonoscope can be visualized using the Euler angles evaluated from the sensor network suggested and the shape of serial link estimated from the kinematics chain model.

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