FEATURE Machine vision
GET TO GRIP WITH BIN PICKING TASKS
Thomas Huenerfauth, Portfolio Manager Vision synthetically generated data and minimal parameterisation effort.”
These special properties make shape-based matching ideal for demanding bin picking applications.
MVTec Software explains how machine vision sustainably improves pick-and-place and bin picking applications
A
can no longer do without robot-assisted gripping processes. While pick-and-place
applications require objects to be securely gripped and placed elsewhere, bin picking is more complex: the objects to be gripped are usually lying in disorder and sometimes on top of each other in containers, which impossible. This where the new Deep 3D Matching technology from MVTec comes in. It recognises the exact position of objects even Within the industrial value chain, there is a multitude of applications in which robots pick-and-place applications, objects are picked up at one location (pick) and placed at another (place). This process is relevant in all stages of production, such as manufacturing, assembly, quality inspection, and packaging. For example, robots pick components from a conveyor belt or pallet, separate them, and
prepare them for further production steps. Pick-and-place applications are also used in intralogistics, such as when picking items from a warehouse.
Other typical applications include placing components on circuit boards in electronics manufacturing or assembling components the heart of many pick-and-place systems is machine vision software combined with one or more cameras for reliable detection of the objects to be gripped. Pick-and- place technologies are fast and precise and therefore increase production capacity and relieve employees of monotonous and strenuous manual handling tasks. Bin picking is a special type of automated gripping, and places high demands on the entire process: the objects to be gripped are usually lying in the bin in a disorderly manner and sometimes overlap. Furthermore, the containers often contain The robot must pick up all these objects safely and with high precision. An essential prerequisite for this is that it can reliably recognise the corresponding parts and locate them with pinpoint accuracy by utilising powerful machine vision software. MVTec Software has developed various machine vision methods for realising both regular pick-and-place and bin picking applications: a commonly used method is shape-based matching. This method enables particularly accurate and robust localisation of a wide variety of objects in real time. The decisive advantage of this technology is that it delivers very robust and sub-pixel- accurate recognition rates even under rotated, scaled, or partially covered objects.
10 June 2025 | Automation
Other important technologies include 3D-based vision methods such as perspective matching. This allows the objects in three-dimensional space to be determined with high precision. Surface- based 3D matching and MVTec’s 3D Gripping Point Detection technology deliver similarly good results. The latter can also be used to reliably detect and grasp objects whose appearance is not known in advance. The method can identify possible gripping surfaces for vacuum suction cups on the objects so that the robot can pick them up precisely.
The most reliable results in bin picking applications are achieved using methods has developed a new method called Deep 3D Matching. This feature combines deep learning algorithms with rule-based methods, enabling highly robust recognition rates. A special feature is that just a few locating objects in three-dimensional space. This saves costs, as only inexpensive 2D cameras are needed. The more cameras are used, the more robust the recognition rates become. Yet another advantage is that the required number of cameras can be added image data can be used for training as well. These images can automatically be produced in large quantities and at low cost using the CAD data of the objects to be recognised. Furthermore, users save time and money, as the images do not need to be labelled. In addition, only a small amount of parameterisation is required to achieve robust recognition rates.
MVTec Software
www.mvtec.com
automationmagazine.co.uk
GET TO GRIP WITH BIN PICKING TASKS
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