Tips for successfully integrating machine vision systems in robotics

Oct. 13, 2014
Prior to designing a vision system for a robotics application, it is important to ensure that pass and fail images are sufficiently differentiated, and that the system is trained to focus on the features of the pass images.  

Prior to designing a vision system for a robotics application, it is important to ensure that pass and fail images are sufficiently differentiated, and that the system is trained to focus on the features of the pass images. Our expert speaker, Jeff Boeve of JR Automation, will offer tips on this and more in a webcast on December 9.

In addition to discussing the importance of the pass features and the vision system’s training to identify these, Boeve will discuss the handling of variation in the images and the appearance of pass/fail parts, while offering advice on controlling the vision system environment and managing unexpected variables. Lastly, he will discuss considerations for lighting, cameras, and software, and how these choices can affect the outcome of your system design, while also devoting time for a question and answer period at the end of the webcast.

Thiswebcast is sponsored by Point Grey.

Webcast information:

Vision technologies for robotics: Application do’s and don’ts
December 9, 2014
11:00 AM EST (Approximately one hour)
Jeff Boeve, JR Automation

Click here for registration information.

Also check out:
Vision-guided robot learning to fly real airplanes
Will the robotics market quadruple by 2025?
Industrial Automation: Robots and vision team for photonic devices assembly

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About the Author

James Carroll

Former VSD Editor James Carroll joined the team 2013.  Carroll covered machine vision and imaging from numerous angles, including application stories, industry news, market updates, and new products. In addition to writing and editing articles, Carroll managed the Innovators Awards program and webcasts.

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