A Robot Localization Framework Using CNNs for Object Detection and Pose Estimation Article Swipe
Lukas Hoyer
,
Christoph Steup
,
Sanaz Mostaghim
·
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1109/ssci.2018.8628752
YOU?
·
· 2018
· Open Access
·
· DOI: https://doi.org/10.1109/ssci.2018.8628752
External localization is an essential part for the indoor operation of small or cost-efficient robots, as they are used, for example, in swarm robotics. We introduce a two-stage localization and instance identification framework for arbitrary robots based on convolutional neural networks. Object detection is performed on an external camera image of the operation zone providing robot bounding boxes for an identification and orientation estimation convolutional neural network. Additionally, we propose a process to generate the necessary training data. The framework was evaluated with 3 different robot types and various identification patterns. We have analyzed the main framework hyperparameters providing recommendations for the framework operation settings. We achieved up to 98% [email protected] and only 1.6° orientation error, running with a frame rate of 50 Hz on a GPU.
Related Topics
Concepts
Artificial intelligence
Convolutional neural network
Computer science
Robot
Pose
Bounding overwatch
Orientation (vector space)
Computer vision
Process (computing)
Object (grammar)
Identification (biology)
Hyperparameter
Swarm robotics
Object detection
Frame (networking)
Frame rate
Minimum bounding box
Pattern recognition (psychology)
Image (mathematics)
Mathematics
Telecommunications
Operating system
Biology
Botany
Geometry
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.1109/ssci.2018.8628752
- OA Status
- green
- Cited By
- 1
- References
- 35
- Related Works
- 20
- OpenAlex ID
- https://openalex.org/W2894575044
All OpenAlex metadata
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https://openalex.org/W2894575044Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.1109/ssci.2018.8628752Digital Object Identifier
- Title
-
A Robot Localization Framework Using CNNs for Object Detection and Pose EstimationWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
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2018Year of publication
- Publication date
-
2018-11-01Full publication date if available
- Authors
-
Lukas Hoyer, Christoph Steup, Sanaz MostaghimList of authors in order
- Landing page
-
https://doi.org/10.1109/ssci.2018.8628752Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/1810.01665Direct OA link when available
- Concepts
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Artificial intelligence, Convolutional neural network, Computer science, Robot, Pose, Bounding overwatch, Orientation (vector space), Computer vision, Process (computing), Object (grammar), Identification (biology), Hyperparameter, Swarm robotics, Object detection, Frame (networking), Frame rate, Minimum bounding box, Pattern recognition (psychology), Image (mathematics), Mathematics, Telecommunications, Operating system, Biology, Botany, GeometryTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
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2020: 1Per-year citation counts (last 5 years)
- References (count)
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35Number of works referenced by this work
- Related works (count)
-
20Other works algorithmically related by OpenAlex
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| publication_date | 2018-11-01 |
| publication_year | 2018 |
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