Object Depth and Size Estimation using Stereo-vision and Integration with SLAM Article Swipe
Layth Hamad
,
Muhammad Asif Khan
,
Amr Mohamed
·
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2409.07623
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2409.07623
Autonomous robots use simultaneous localization and mapping (SLAM) for efficient and safe navigation in various environments. LiDAR sensors are integral in these systems for object identification and localization. However, LiDAR systems though effective in detecting solid objects (e.g., trash bin, bottle, etc.), encounter limitations in identifying semitransparent or non-tangible objects (e.g., fire, smoke, steam, etc.) due to poor reflecting characteristics. Additionally, LiDAR also fails to detect features such as navigation signs and often struggles to detect certain hazardous materials that lack a distinct surface for effective laser reflection. In this paper, we propose a highly accurate stereo-vision approach to complement LiDAR in autonomous robots. The system employs advanced stereo vision-based object detection to detect both tangible and non-tangible objects and then uses simple machine learning to precisely estimate the depth and size of the object. The depth and size information is then integrated into the SLAM process to enhance the robot's navigation capabilities in complex environments. Our evaluation, conducted on an autonomous robot equipped with LiDAR and stereo-vision systems demonstrates high accuracy in the estimation of an object's depth and size. A video illustration of the proposed scheme is available at: \url{https://www.youtube.com/watch?v=nusI6tA9eSk}.
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Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2409.07623
- https://arxiv.org/pdf/2409.07623
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4403663123
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4403663123Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2409.07623Digital Object Identifier
- Title
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Object Depth and Size Estimation using Stereo-vision and Integration with SLAMWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-09-11Full publication date if available
- Authors
-
Layth Hamad, Muhammad Asif Khan, Amr MohamedList of authors in order
- Landing page
-
https://arxiv.org/abs/2409.07623Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2409.07623Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
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https://arxiv.org/pdf/2409.07623Direct OA link when available
- Concepts
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Computer vision, Artificial intelligence, Object (grammar), Computer science, Stereopsis, Estimation, Engineering, Systems engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
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0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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