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Brave new world of ‘SensorApps’

by Lee Mclaughlan
September 16, 2020
in 3D Vision, Featured, Machine Vision, Measurement & Testing, News Feed, Sensors
Share this story

Developers have access to industry-standard image processing libraries including HALCON.  They can work with their preferred programming technologies including graphical flow Editor, Lua scripting tools as well as C++ or Java.  There are many integrated support functions such as auto completion, so that programmable sensor app developments will insert themselves easily into existing development processes.

Helpful utilities such as emulators, debuggers, resource monitors, and an extensive range of documentation and demo apps also make the development process easy. All software components are combined by the PackageBuilder into a single package that safely defines access rights.  Previously developed ‘Apps’ can be adapted without having to start from scratch, then set-up and configure as required.

Meanwhile end-users can dispense with costly and time-consuming programming by downloading and adapting a ready-made SensorApp that already has most of the hard work done for them. As a result, set up time is dramatically reduced, rapid product changeovers are easily accommodated, and localised edge-based sensor solutions can be easily configured using Sensor Integration Machines.

Robot Guidance

Sick sensor apps
SICK’s TrispectorP1000 3D camera is easily customised for robot belt picking applications.

This is all being made possible by greater accessibility to ‘all-in-one’ intelligent vision sensors, such as SICK’s fully programmable TrispectorP1000 3D vision camera. One of the first Apps to be developed was the SICK Trispector P Beltpick, a complete vision-guided belt-picking solution for industrial and collaborative robots. It offers the improved z-axis control available through 3D vision, so products with complex profiles can be picked from variable heights without risk of damage.

More recently, SICK launched an innovative 3D SensorApp that has enabled rapid, damage-free guidance of automated and driver-assisted high-bay forklifts into pallet pockets, as well as the precise and efficient pick-up of dollies by automated guided vehicles (AGVs).

The SICK Pallet Pocket and SICK Dolly Positioning SensorApps run on SICK’s Visionary T-AP 3D time-of-flight snapshot camera.  The new SensorApps work by positioning the camera in front of the pocket or dolly chassis. Using a single shot of light, the SICK Visionary T-AP 3D camera captures a 3D image, then pre-processes and evaluates the co-ordinates of the pallet pocket or space under the dolly, before outputting to the vehicle controller.  The information can also be sent to a driver display to aid manual forklift operation, particularly useful in high-bay warehouses.

Continue reading article…

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Tags: 3D visionautonomous vehiclesinspection applicationsMachine VisionsensorsSICK
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