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Scene Identification based onConcept LearningBeatrice van Eden
- Part time PhD Student at the University of the Witwatersrand.- Fulltime employee of the Council for Scientific and Industrial Research.
Index• Broad problem statement Give an overview of the researchI am busy with. • Identify items in a scene 3D Current work on the project.
• Continued workHighlights of some of the reading I did.
Broad Problem Statement
• How can we give a mobile robot the capability to continuously and autonomously form concepts of its environment?
Identify items in a scene 3D
• Marius Muja of University of British Columbia (2009)• Manipulating tabletop objects: one of the main tasks of a robot in
a household environment• Setting/cleaning the table• Serving drinks
• Usual tabletop objects are difficult (no texture, transparent)• Techniques based on local features fail• RANSAC – Random sample consensus (voting scheme to find optima fitting result)
Identify items in a scene 3D • Grasping of objects requires precise object localization• Bounding box around the object is not enough• Know the grasp
• Extended the 2D chamfer matching approach to 3D• Chamfer – calculates distance between two images
Identify items in a scene 3D • Two stage approach• Bottom-up object localization
• Determines probable object locations• Table plane detection and removal• Point cloud clustering
• Top down model fitting• Determines exact object pose and identity• Find the model with the best correspondence to the point cloud• ICP-like (Iterative Closest Point) algorithm
Identify items in a scene 3D • \tabletop objects" package• The 3D model fitter determines
• Object identity• Object pose• Grasp pose• Object mesh - used in the planning stage for a more precise collision
map• Integrated with the planning pipeline
Continued work• Backtracks a bit.• Go back to the technical sections of papers I already read• Go through the pseudo code of the work in this papers• Test one or two more things I am unsure about in the 2D object
detection I showed you last week.
Thank you