G-nous Tech develops tailored Computer Vision and Machine Learning algorithms to enable robotic systems to perform non-repetitive and non-monotonous pick and place tasks.
Intelligent pick and place robots have been becoming increasingly adopted in factories to improve efficiency, productivity and capability of industrial processes. By means of a wide variety of Computer Vision algorithms, robots can deal with different complex situations where the objects to be picked are randomly placed.
G-nous Intelligent Robotic Pick and Place solutions exploit Computer Vision to enable robots identifying, grasping and moving objects from one place to another.
- Packaging – Robots with smart 2D and 3D vision systems allow the picking of objects and placing them in boxes or on conveyor belts.
- Assembly – smart robots speed up assembly processes and increase accuracy.
- Bin Picking – Robots equipped with 3D structured-light vision systems pick up objects from a bin, which can be difficult for humans due to the high degree of accuracy and precision required.
- Mixed Palletizing – Robots are able to pick randomly-piled and randomly placed objects tightly regardless of their size, pattern, or weight.
G-nous Tech has been carrying out research and development activities for the identification and integration of complex 3D vision systems in robotic pick and place applications.
Moreover, G-nous Tech has been developing Computer Vision algorithms for object detection and instance segmentation in order to compute the optimal pose of the robot for object grasping.
Manufacturing companies, logistics and distribution companies, Warehouses.
Every company with a production process.
Partners: Universal Robots