Pick & Place / Bin Picking
Intelligent optical image capture systems for exact-position component processing.
GedonSoft GmbH is your software partner in the field of “machine vision” with self-learning algorithms – deep learning – to automate mechanical,
Application of pick & place / bin picking with image capture systems offer you:
- exact identification of alignment, shape and position of objects
- error-free, correct positioning in the required cycle time
- recognition of workpiece rotation and alignment
- camera and robot-controlled pre-separation
- automated workpiece feeding
- exact-position object processing
Artificial intelligence (AI), neural networks and deep learning frameworks
enables to reliably identify a wide variety of objects solely on the basis of optical feature spaces, to precisely determine their position and reliably detect
production errors. KI methods offer easily and robust recognition rates by detailed analysis of a very large amount of image data (big data).
The image processing procedure developed by us allows diverse task automation in the area of pick & place / bin picking with short recognition time
and maximum recognition reliability.
- measurement of geometric structure
- object and position recognition
- completeness testing
- inspection tasks
Various pick and place / bin picking tasks can be automated at higher speed and with exact repeatability with the industrial image processing
procedures as developed by us.
Pick & place / bin picking via an intelligent, self-learning – deep learning – image processing system makes new, flexible and cost-effective
automation of production processes possible.
Together with you, we analyze your requirements and support you efficiently and professionally in planning and implementing your image processing
project by using industrially suited cameras, custom-fit software, optimal objectives and illumination.
We support you in the implementation of your project with tailored solutions.
You’re interested in one of our services? We will gladly advise you!
Phone: +49421-2781835 or email@example.com