Session WedAT1 Pegaso A Wednesday, October 10, 2012 ... - Lirmm

Session WedGT6 Gemini 3 Wednesday, October 10, 2012, 17:30–18:30
Localization and Mapping III
Chair Jun Miura, Toyohashi Univ. of Tech.
Co-Chair
17:30–17:45 WedGT6.1
Efficient Search for Correct and Useful
Topological Maps
Collin Johnson and Benjamin Kuipers
EECS, University of Michigan, USA
• We present an algorithm for probabilistic
topological mapping.
• Perform a heuristic search of a tree of
maps.
• Runs online.
• Never prunes consistent topological map
hypotheses so correct map can always be
found.
Top: Topological map built by our
algorithm
Bottom: Hypotheses expanded
by our algorithm vs. brute force
18:00–18:15 WedGT6.3
Accurate 3D maps from depth images and
motion sensors via nonlinear Kalman filtering
Thibault Hervier, Silvère Bonnabel, François Goulette
Centre de Robotique - CAOR, MINES ParisTech, France
• Use of depth images as localization
sensors
• Combined with ICP
• Analysis of ICP results
• Data fusion with non-linear filtering:
Invariant Extended Kalman Filter
• Natural, robust, handles SE3
• Experiments with Kinect sensor and
gyros shows improvement in accuracy
of localization and map building
Depth images
ICP
Localization
& covariance
Non linear Kalman
filtering (IEKF)
3D maps
Experimental setup
Motion data
(gyros)
17:45–18:00 WedGT6.2
Accurate On-Line 3D Occupancy Grids
Using Manhattan World Constraints
Brian Peasley and Stan Birchfield
Electrical and Computer Engineering Dept, Clemson University, USA
Alex Cunningham and Frank Dellaert
School of Interactive Computing, Georgia Institute of Technology, USA
• Large dense 3D occupancy grids
are constructed from RGB-D data
• Factor graphs are used to combine
odometry and visual data
constrained by a Manhattan World
assumption
• Manhattan World assumption
removes rotational drift – no need
for loop closure
• Large 3D maps of environments
efficiently stored using an octree
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
–188–
3D and 2D reconstruction of
a large building environment
18:15–18:30 WedGT6.4
Fourier-based Registrations for Two-Dimensional
Forward-Looking Sonar Image Mosaicing
Natalia Hurtos, Xavier Cufí and Joaquim Salvi
Computer Vision and Robotics Group, University of Girona, Spain
Yvan Petillot
Ocean Systems Laboratory, Heriot -Watt University, U.K.
• Phase correlation method is used to
address the registration of forward-looking
sonar images.
• Registrations from loop-closing situations
and areas without abundant features are
feasible.
• By integrating the result of pairwise
registrations into a pose-based graph
optimization a consistent sonar mosaic is
generated.
• The vehicle motion in x,y and heading can
be also estimated from the registrations.