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

Session WedDT6 Gemini 3 Wednesday, October 10, 2012, 14:00–15:00
Mapping III
Chair
Co-Chair
14:00–14:15 WedDT6.1
Sensor Fusion for Flexible Human-Portable
Building-Scale Mapping
Maurice F. Fallon, Hordur Johannsson,
Jonathan Brookshire, Seth Teller, John J. Leonard
Computer Science and Artificial Intelligence Laboratory, MIT, USA
• Man-portable sensor rig for
Biohazard Site Assessment teams
• LIDAR based multi-floor mapping
algorithm using iSAM
• Re-localization using visual
appearance
• Floor tracking using a pressure
sensor
14:30–14:45 WedDT6.3
Efficient Map Merging Using a Probabilistic
Generalized Voronoi Diagram
Sajad Saeedi ♦ , Liam Paull ♦ , Michael Trentini ♦♦ , Mae Seto ♦♦ and
Howard Li ♦
♦ Electrical and Computer Engineering, University of New Brunswick, Canada
♦♦ Defence Research and Development Canada, Canada
• One of the problems for multi-robot SLAM
is that the robots only know their positions
in their own local coordinate frames, so
fusing map data can be challenging.
• In this research, a probabilistic version of
the Generalized Voronoi Diagram (GVD),
called the PGVD, is used to determine the
relative transformation between maps and
fuse them.
• The new method is effective for finding
relative transformations quickly and
reliably. In addition, the novel approach
accounts for all map uncertainties in the
fusion process.
Probabilistic GVD of two partial
maps which are used for map
fusion
14:15–14:30 WedDT6.2
Fast Voxel Maps with Counting Bloom Filters
Julian Ryde and Jason J. Corso
Computer Science and Engineering, University at Buffalo, USA
• Bloom filters applied to accelerate look up
speed of voxel occupancy in maps for
mobile robots
• Probabilistic data structure
•Small probability of false positive
•False negatives always correct
• Fast sparse voxel occupancy lookup
•3 times faster than efficient hash table
•Within 10% speed of dense array
• Tested for 3D SLAM with point cloud data
and no impact on mapping accuracy
observed
• Works with very large maps that do not fit
in computer RAM
14:45–15:00 WedDT6.4
A Pipeline for Structured Light Bathymetric
Mapping
Gabrielle Inglis, Clara Smart, Ian Vaughn and Chris Roman
Department of Ocean Engineering, University of Rhode Island, USA
• A method for creating micro-bathymetric
maps using structured light imaging is
presented
• Algorithms for segmentation of the laser
image and in-situ calibration of the
imaging sensor are developed
• Sub-map based simultaneous localization
and mapping (SLAM ) is adapted to solve
for navigation
• High resolution maps meet or exceed
standards of state of the art acoustic
methods
2012 IEEE/RSJ International Conference on Intelligent Robots and Systems
–156–
Archaeological structured light
survey gridded at 1 cm.