By Topic

Learning-based configuration estimation of a multi-segment continuum robot

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Austin Reiter ; Dept. of Computer Science, Columbia University, New York, NY 10027, USA ; Andrea Bajo ; Konstantinos Iliopoulos ; Nabil Simaan
more authors

In this paper, we present a visual learning algorithm for estimating the configuration of a multisegment continuum robot designed for surgery. Our algorithm interpolates a stereo visual feature descriptor manifold using Radial Basis Functions (RBFs) to estimate configuration pose angles. Results are shown on a 3-segment snake robot, where rotational accuracy in the range of 1° -2° is achieved.

Published in:

2012 4th IEEE RAS & EMBS International Conference on Biomedical Robotics and Biomechatronics (BioRob)

Date of Conference:

24-27 June 2012