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Learning grasping points with shape context

Bohg, Jeannette (author)
KTH,Centrum för Autonoma System, CAS,Datorseende och robotik, CVAP
Kragic, Danica (author)
KTH,Centrum för Autonoma System, CAS,Datorseende och robotik, CVAP
 (creator_code:org_t)
Elsevier BV, 2010
2010
English.
In: Robotics and Autonomous Systems. - : Elsevier BV. - 0921-8890 .- 1872-793X. ; 58:4, s. 362-377
  • Journal article (peer-reviewed)
Abstract Subject headings
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  • This paper presents work on vision based robotic grasping. The proposed method adopts a learning framework where prototypical grasping points are learnt from several examples and then used on novel objects. For representation purposes, we apply the concept of shape context and for learning we use a supervised learning approach in which the classifier is trained with labelled synthetic images. We evaluate and compare the performance of linear and non-linear classifiers. Our results show that a combination of a descriptor based on shape context with a non-linear classification algorithm leads to a stable detection of grasping points for a variety of objects.

Subject headings

NATURVETENSKAP  -- Data- och informationsvetenskap (hsv//swe)
NATURAL SCIENCES  -- Computer and Information Sciences (hsv//eng)

Keyword

Grasping
Shape context
Affordances
SVM
Information technology
Informationsteknik

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ref (subject category)
art (subject category)

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Bohg, Jeannette
Kragic, Danica
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NATURAL SCIENCES
NATURAL SCIENCES
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Robotics and Aut ...
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Royal Institute of Technology

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