The robot guide is an artificial vision system
that can guide the robot to perform an action
using the camera

In the industrial sector, vision systems for robot guidance play a fundamental role because they allow robots to follow trajectories dictated by image interpretation, giving flexibility and autonomy to the production line.
Thanks to 2D and 3D cameras, robots are able to recognize the position and orientation of parts and the context in which they are located, adapting their trajectory in real time.
Specialvideo also creates robot guides equipped with artificial intelligence, as in the challenging case of automatic ham greasing.

Freeing the robot from the constraint of depending on perfect component positioning is particularly useful in pick & place operations, where parts may be disordered on a conveyor belt or inside containers, and the robot becomes capable of visually identifying them in order to pick them.
Specialvideo has experience in the simultaneous management of many robots, in production contexts with a rate of over 1000 pieces per minute, with products traveling in many rows, even if not aligned.

We can manage a multi-belt line with a single vision system, even with belts running at different speeds, and coordinate multiple robots simultaneously.

Vision is equally valuable in assembly and machining, because it allows the robot to distinguish product details, orient itself accurately in space, and verify that the operation has been performed correctly.
In many production lines, vision systems are also integrated for palletizing and depalletizing, because they allow boxes or objects to be recognized even when they are not perfectly aligned, ensuring dynamic adaptation to variable formats and arrangements.

Robot guidance also supports quality control and non-contact measurements, allowing the camera to be moved to the appropriate location for defect detection, or transporting parts to special stations for image acquisition with specially designed lighting.
The system then processes the images, also taking advantage of movement times, to integrate with real-time responses.
Inspection can therefore be combined with corrective actions by the robot itself, such as the separation of defective parts.

Even in difficult contexts such as narrow workspaces and high-speed moving products, we bring our years of experience and continuous innovation to the field.

In the industrial field robot guidance systems provide the ability to see objects and then allow to pick up the pieces in random positions or to perform a machining path which is not the default. The use of robots in robotised guides therefore allows to realize automation systems which are extremely versatile and with reduced tooling times.

In order to get the best performance, Specialvideo has developed special calibration algorithms: Calibration is the function which allows the vision system to know the reference system of the robot and, at the same time to correct perspective distortion of the objective. The perspective deformation compensation is required especially in cases in which the camera is positioned close to the pieces, or it is inclined with respect to the work plane.

The robot guidance system, developed by SPECIALVIDEO, can be configured to work with still or moving parts and also with pieces in contact with each other and partially occluded. It can be also equipped with functions for quality control, to detect the presence of defective parts and consequently manage the pieces deviation.

The main application concerns the removal of pieces on the conveyor belt (2D), arranged in layers on pallets (2D multi-layer), or bulk pieces where it is necessary to use three-dimensional techniques (3D).

Features

  • Identification of objects in random position
  • Multi-faceted automation systems
  • Special algorithms to compensate the lens perspective deformation
  • Robot guidance systems for stationary moving parts, or partially occluded
  • Defects detection
  • Management of waste

Request information: free quote with feasibility study on samples