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Real-time 3D SLAM for Humanoid Robot considering Pattern Generator Information

O. Stasse, Andrew Davison, R. Sellaouti, K. Yokoi

Conference or Workshop Paper
IEEE/RSJ International Conference on Intelligent Robots and Systems
October, 2006
pp.348–355
IEEE/RSJ
ISBN 1-4244-0259-X
DOI 10.1109/IROS.2006.281645
Abstract

Humanoid robotics and SLAM (Simultaneous Lo-

calisation and Mapping) are certainly two of the most significant

themes of the current worldwide robotics research effort, but the

two fields have up until now largely run independent parallel

paths, despite the obvious benefit to be gained in joining the

two. The next major step forward in humanoid robotics will be

increased autonomy, and the ability of a robot to create its own

world map on the fly will be a significant enabling technology.

Meanwhile, SLAM techniques have found most success with

robot platforms and sensor configurations which are outside of

the humanoid domain. Humanoid robots move with high linear

and angular accelerations in full 3D, and normally only vision

is available as an outward-looking sensor. Building on recently

published work on monocular SLAM using vision, and on pattern

generation, we show that real-time SLAM for a humanoid can

indeed be achieved. Using HRP-2, we present results in which a

sparse 3D map of visual landmarks is acquired on the fly using

a single camera and demonstrated loop closing and drift-free 3D

motion estimation within a typical cluttered indoor environment.

This is achieved by tightly coupling the pattern generator, the

robot odometry and inertial sensing to aid visual mapping within

a standard EKF framework. To our knowledge this is the first

implementation of real-time 3D SLAM for a humanoid robot

able to demonstrate loop closing.

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