Vision-guided robotics for pick-and-place applications
In industrial pick-and-place applications, vision-guided robots (VGR) are typically robotic arms with integrated machine vision systems. The machine vision system helps the robot discover the location of an object in order to guide the robot to a desired point for pick and place.
There are many complicated components that go into a VGR system and it’s easy to overlook subtle but important aspects of design and installation. Without serious application analysis and system specification, VGR systems will not provide the accuracy or reliability they’re expected to.
An inaccurate or improperly functioning VGR will make mistakes, which leads to downtime. This downtime can add up quickly, especially in high-volume processes.
What pick-and-place applications are VGR systems used for?
VGR systems are typically used for high-volume, highly repeatable processes. Some of the more common applications include:
- Loading/unloading parts from conveyors and feeding systems
- Loading/unloading nested parts from trays or boxes
- Part placement, assembly, and packaging
- Racking and de-racking
- Palletizing and de-palletizing
- Bin picking of random parts.
Many of these applications require a robotic arm to not only determine the location and orientation of an object, but to determine what the object is in the first place and how to best pick or place it. For this to happen, the vision system must work flawlessly, which is no small task. A large part of finding success with VGR systems is setting up a proper machine vision system.
Successful techniques in vision-guided robotic pick-and-place
Lighting and imaging are key components of a VGR. Even for something as simple as lighting, users have to take several things into account such as:
- The geometry of the light
- The object characteristics in terms of reflection
- The light source characteristics
- The intensity and coverage of the light since VGR applications require large fields of view (FOV)
- The physics of the light’s angle of incidence and angle of reflection.
There’s a ton of factors to take into account, even for just the lighting. The camera chosen will often involve even more considerations, such as lens characteristics, sensor size, focal length, and more, which are all application-specific.
This article originally appeared on the AIA blog. The AIA is a part of the Association for Advancing Automation (A3), a CFE Media content partner. Edited by Carly Marchal, content specialist, CFE Media, firstname.lastname@example.org.
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