Bin Picking Success Rate Depending on Sensor Sensitivity Article Swipe
Petr Doležel
,
Jan Pidanič
,
Tomáš Zálabský
,
Miroslav Dvořák
·
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/carpathiancc.2019.8766009
YOU?
·
· 2019
· Open Access
·
· DOI: https://doi.org/10.1109/carpathiancc.2019.8766009
The goal of this contribution is to determine correlation between an applied sensor for object registration and the success rate of the bin-picking problem. In most applications of a bin picking problem in industry, the procedure consists of two consecutive steps. The first step provides an initial guess of both position and rotation angle of the object to be registered, while the second one improves the exact pose accuracy, as required in following tasks. The second step can be, among others, implemented by the Iterative Closest Point Algorithm (ICP). It is well known that the ICP algorithm is very sensitive to the initial guess of the position and rotation angle of the object. Another interesting feature, especially from the technician’s point of view, is the sensitivity of the ICP algorithm in relation to the applied sensor. Therefore, one particular bin picking application, involving complex irregular objects, is examined in this paper. Various kinds of sensors for 3D scene reconstruction are employed and, as a result of this contribution, a comprehensive set of relations between sensor quality and the ICP algorithm sensitivity is formulated.
Related Topics
Concepts
Bin
Iterative closest point
Sensitivity (control systems)
Rotation (mathematics)
Computer science
Position (finance)
Object (grammar)
Point (geometry)
Bin packing problem
Computer vision
Algorithm
Set (abstract data type)
Artificial intelligence
Feature (linguistics)
Mathematics
Point cloud
Engineering
Economics
Philosophy
Finance
Geometry
Programming language
Linguistics
Electronic engineering
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1109/carpathiancc.2019.8766009
- OA Status
- green
- Cited By
- 7
- References
- 13
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W2964081265
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W2964081265Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/carpathiancc.2019.8766009Digital Object Identifier
- Title
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Bin Picking Success Rate Depending on Sensor SensitivityWork title
- Type
-
articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2019Year of publication
- Publication date
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2019-05-01Full publication date if available
- Authors
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Petr Doležel, Jan Pidanič, Tomáš Zálabský, Miroslav DvořákList of authors in order
- Landing page
-
https://doi.org/10.1109/carpathiancc.2019.8766009Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://hdl.handle.net/10195/75126Direct OA link when available
- Concepts
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Bin, Iterative closest point, Sensitivity (control systems), Rotation (mathematics), Computer science, Position (finance), Object (grammar), Point (geometry), Bin packing problem, Computer vision, Algorithm, Set (abstract data type), Artificial intelligence, Feature (linguistics), Mathematics, Point cloud, Engineering, Economics, Philosophy, Finance, Geometry, Programming language, Linguistics, Electronic engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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7Total citation count in OpenAlex
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2024: 2, 2023: 1, 2022: 2, 2021: 1, 2020: 1Per-year citation counts (last 5 years)
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13Number of works referenced by this work
- Related works (count)
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10Other works algorithmically related by OpenAlex
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