By Topic

3D grid and particle based SLAM for a humanoid 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
$31 $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

4 Author(s)
Nosan Kwak ; Joint Robot. Lab., Nat. Inst. of Adv. Ind. Sci. & Technol., Tsukuba, Japan ; Stasse, O. ; Foissotte, T. ; Yokoi, K.

Necessity to recognize the world like a home environment by a humanoid robot has recently been arisen for daily usages. As an observation sensor, stereo vision is the most common device for a humanoid robot to obtain the environmental data, but it is more erroneous than a laser sensor. To overcome the inaccuracy of stereo vision, we propose a particle-based SLAM technique so that the SLAM posterior is estimated by multiple hypotheses. The major difficulty of the particle-based SLAM with 3D grid maps is the high computational cost. To reduce the computational cost, we also propose a scheduling method for the time when to match and for particles that engage in the matching process. Through experiments with a humanoid robot, HRP-2, it is shown that the proposed approach can reduce the computational cost while preserving estimation accuracy.

Published in:

Humanoid Robots, 2009. Humanoids 2009. 9th IEEE-RAS International Conference on

Date of Conference:

7-10 Dec. 2009