internship presentation - robot operating system...internship presentation marius muja august 26,...
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Internship Presentation
Marius Muja
August 26, 2009
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What’s been keeping me busy?
Milestone 2
Far outlet detectionDoor handle detection
Tabletop object detection
2D Chamfer matching3D Model fitting
Integrating FLANN in OpenCV
PR2 Challenge
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Far outlet detection
Uses the stereo camera andbase laser to identify locationand 3D pose of power outlets
Outlet candidates obtained bysegmenting the disparity image
Wall pose computed form thebase laser scan
List of outlet candidates isfiltered using position, size andorientation priors
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Far outlet detection
Outlet candidate patches arerectified to obtain a frontal view
Outlet identity is confirmedusing a template matchingalgorithm
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Door handle detection
Initial detection using a boostedcascaded classifier of haarfeatures
False positives eliminated usingposition and size priors
Detections clustered acrossseveral frames for increasedrobustness
3D location of handle fromstereo
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Tabletop object detection
Manipulating tabletop objects: one of the main tasks of arobot in a household environment
Setting/cleaning the tableServing drinks
Usual tabletop objects are difficult (no texture, transparent)
Techniques based on local features fail
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Ikea objects dataset
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2D Chamfer matching
Approach for finding the bestmatch of a contour model to anedge image
Contours can be strongindicator of object’s identity
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2D Chamfer matching
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3D model fitting
Grasping of delicate (glass)objects requires precise objectlocalization
Just a bounding box aroundthe object is not enoughWe must also know the grasplocation for a specific object
Extended the 2D chamfermatching approach to 3D
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3D model fitting
Two stage approach
Bottom-up object localization
Determines probable objectlocationsTable plane detection andremovalPoint cloud clustering
Top down model fitting
Determines exact object poseand identityFind the model with the bestcorrespondence to the pointcloudICP-like (Iterative ClosestPoint) algorithm
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3D model fitting
“tabletop objects” package
The 3D model fitter determines
Object identityObject poseGrasp poseObject mesh - used in theplaning stage for a moreprecise collision map
Integrated with the planingpipeline
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PR2 challenge
Applied the 3D model fittingapproach for detectingjuice/watter bottles
Used the tilting laser pointcloud (much more sparse thanthe laser point cloud)
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Model capture
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Others
Integrated FLANN in OpenCV
FLANN - Fast Library for Approximate Nearest Neighborsfast nearest-neighbor searching in high dimensional spaces
PR2 teleoperation using a phone
based on Asterisk open source PBXcall the robot on the phone and send it to a specific officeother use cases possible: eg. deliver a message
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Work in progress
Improving bottom-up part of object detection pipeline
3D features voting for object pose
3D object tracking
Neigborhood indexing for large point cloud structures
Sparse voxel grid indexingBenchmarks for the different index types
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Thank you!