Vision sensor for pick-and-place applications
The FQ-M vision sensor by Omron comes with Ethernet and EtherCAT embedded for easy integration and an incremental encoder for tracking and calibration.
Omron introduced a vision sensor developed specifically to meet the needs of pick-and-place applications. Highly compact, and with a processing speed of 5,000 pieces per minute even with full 360 degree rotation, the FQ-M vision sensor comes with Ethernet and EtherCAT embedded for ease of integration into any environment, and includes an incremental encoder for easy tracking and calibration. The FQ-M is configured for guidance of dynamic pick-and-place robots using Omron’s Sysmac Studio software, and is complemented by the palm-sized TouchFinder console for local monitoring and access to functions and settings.
The FQ-M is a smart camera that meets all the needs of demanding object recognition and tracking applications, combining a camera, image processing functionality and flexible communications options into a single compact package.
The FQ-M vision sensor tightly integrates core automation components with a common network and a single programming and configuration interface. It communicates with other devices either via EtherCAT or via standard Ethernet, or a combination of the two.
Object detection is based on a newly developed contour-based search algorithm which ensures the highest reliability, regardless of changing lighting conditions, reflection and object inclination. The algorithm can even cope with overlapped or partially hidden objects. With this high performance algorithm and the high speed image processing capability, the FQ-M can detect up to 32 pieces at once with absolute stability, and 5,000 pieces per minute. The incremental encoder interface simplifies initial calibration of the system, and enables on-the-fly tracking for tightly synchronized control. The FQ-M is able to output position coordinates and the corresponding encoder values, and is able to manage the object queue so that no object’s coordinates are duplicated.
Set-up of the FQ-M vision sensor is performed through the Vision Editor of the Sysmac Studio software, which provides intuitive, icon-driven configuration that makes it easy to achieve the optimum vision setting. The Vision Editor also provides comprehensive trending and logging functions. For easy integration into robot pick-and-place systems, the communication wizard makes it easy to configure any robot protocol either as a server or as a client without complex programming.
For ease of monitoring and for access to parameters and settings, the TouchFinder console provides a 3.5-in. TFT color touch screen. Users can view images in real time, zoom in, zoom out and freeze images for closer manual inspection. The TouchFinder can also show a variety of measurements, including the last result, the last no-go result, a trend monitor and histograms. It can also log the data from measurement results and measured images. Users navigate through the various functions via the intuitive touch screen interface.
Measuring just 110 x 75 x 50 mm, the FQ-M vision sensor is compact enough to make mounting simple in even the most challenging automation environments. For ultimate flexibility, the FQ-M provides a standard C-Mount lens attachment, enabling users to select from a wide range of compatible lenses for optimized system performance.
Omron Industrial Automation
- Edited by Chris Vavra, Control Engineering, www.controleng.com
Case Study Database
Get more exposure for your case study by uploading it to the Control Engineering case study database, where end-users can identify relevant solutions and explore what the experts are doing to effectively implement a variety of technology and productivity related projects.
These case studies provide examples of how knowledgeable solution providers have used technology, processes and people to create effective and successful implementations in real-world situations. Case studies can be completed by filling out a simple online form where you can outline the project title, abstract, and full story in 1500 words or less; upload photos, videos and a logo.
Click here to visit the Case Study Database and upload your case study.