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6D Object Localization in Car-Assembly Industrial Environment
by
Pateraki, Maria
, Papadaki, Alexandra
in
Accuracy
/ Assembly
/ Assembly lines
/ Assembly-line methods
/ Automobiles
/ Cameras
/ challenging object characteristics
/ Collaboration
/ complex scenes
/ Correspondence
/ Datasets
/ Deep learning
/ Environment models
/ Germany
/ Grasping (robotics)
/ Image processing
/ Indoor environments
/ Industrial applications
/ Industrial research
/ industrial robotic applications
/ Localization
/ machine learning
/ Machine vision
/ Manufacturing
/ Methods
/ Middleware
/ object 6D pose estimation
/ object localization
/ Object recognition
/ Operating systems
/ Pose estimation
/ Production processes
/ Robotics
/ Robots
/ Robots, Industrial
/ Sequences
/ Surface layers
/ Surface properties
/ Teaching methods
/ Workflow
2023
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6D Object Localization in Car-Assembly Industrial Environment
by
Pateraki, Maria
, Papadaki, Alexandra
in
Accuracy
/ Assembly
/ Assembly lines
/ Assembly-line methods
/ Automobiles
/ Cameras
/ challenging object characteristics
/ Collaboration
/ complex scenes
/ Correspondence
/ Datasets
/ Deep learning
/ Environment models
/ Germany
/ Grasping (robotics)
/ Image processing
/ Indoor environments
/ Industrial applications
/ Industrial research
/ industrial robotic applications
/ Localization
/ machine learning
/ Machine vision
/ Manufacturing
/ Methods
/ Middleware
/ object 6D pose estimation
/ object localization
/ Object recognition
/ Operating systems
/ Pose estimation
/ Production processes
/ Robotics
/ Robots
/ Robots, Industrial
/ Sequences
/ Surface layers
/ Surface properties
/ Teaching methods
/ Workflow
2023
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6D Object Localization in Car-Assembly Industrial Environment
by
Pateraki, Maria
, Papadaki, Alexandra
in
Accuracy
/ Assembly
/ Assembly lines
/ Assembly-line methods
/ Automobiles
/ Cameras
/ challenging object characteristics
/ Collaboration
/ complex scenes
/ Correspondence
/ Datasets
/ Deep learning
/ Environment models
/ Germany
/ Grasping (robotics)
/ Image processing
/ Indoor environments
/ Industrial applications
/ Industrial research
/ industrial robotic applications
/ Localization
/ machine learning
/ Machine vision
/ Manufacturing
/ Methods
/ Middleware
/ object 6D pose estimation
/ object localization
/ Object recognition
/ Operating systems
/ Pose estimation
/ Production processes
/ Robotics
/ Robots
/ Robots, Industrial
/ Sequences
/ Surface layers
/ Surface properties
/ Teaching methods
/ Workflow
2023
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6D Object Localization in Car-Assembly Industrial Environment
Journal Article
6D Object Localization in Car-Assembly Industrial Environment
2023
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Overview
In this work, a visual object detection and localization workflow integrated into a robotic platform is presented for the 6D pose estimation of objects with challenging characteristics in terms of weak texture, surface properties and symmetries. The workflow is used as part of a module for object pose estimation deployed to a mobile robotic platform that exploits the Robot Operating System (ROS) as middleware. The objects of interest aim to support robot grasping in the context of human–robot collaboration during car door assembly in industrial manufacturing environments. In addition to the special object properties, these environments are inherently characterised by cluttered background and unfavorable illumination conditions. For the purpose of this specific application, two different datasets were collected and annotated for training a learning-based method that extracts the object pose from a single frame. The first dataset was acquired in controlled laboratory conditions and the second in the actual indoor industrial environment. Different models were trained based on the individual datasets and a combination of them were further evaluated in a number of test sequences from the actual industrial environment. The qualitative and quantitative results demonstrate the potential of the presented method in relevant industrial applications.
Publisher
MDPI AG,MDPI
Subject
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