New software improvements and added functionalities

Improvements

New DeepAL detection engine

• Teach parts fast. No training is required, just show it to the camera and you’ re ready to go!
• Detect the correct orientation of a box based on its color pattern DeepAL is quite tolerant of changing lighting conditions
• Detect plain boxes with no color pattern
• Detect parts in any pattern. Pickit doesn’ t need to know about how the parts are laid out, and the pattern can change from one layer of the pallet to the next
• Detect parts that have moved (and even tilted), as can happen on pallet top layers

Better support for 4-axis robots

• In Pickit 3.2, it’ s easy to enforce this contraint, yet take into account the fact that robot tools often tolerate some tilt without compromising pick success

Teach box model

• This model type is recommended for applications with randomly oriented box-shaped objects of known dimensions, such as billets with a square cross-section
• Whereas before you had to teach a box part by placing it under the camera or uploading a CAD file, now you only need to specify its dimensions, similarly to how it’ s done for cylinders

Flexible pick position

• Some picks tolerate translations along a direction without compromising pick success. Pickit allows specifying this flexible pick position and will exploit it when selecting how to pick a part

More part pickability insights

• Pickit leverages multiple sources of pick flexibility to find valid picks, and you can learn the reason why it was used by inspecting the viewer and objects table