Case Studies

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Robotics - Ensenso N

Self-learning robots solve tasks with the help of an Ensenso 3D camera

Seen, stored, learned

Trying out different behaviours is one of the classic learning methods. Success or failure decides which behaviour is adopted. This principle can be transferred to the world of robots. At the Institute for Intelligent Process Automation and Robotics of the Karlsruhe Institute of Technology (KIT), the Robot Learning Group (ROLE) focuses on various aspects of machine learning. The scientists are investigating how robots can learn to solve tasks by trying them out independently. These methods are used in particular for learning object manipulation, for example for grasping objects in a typical bin picking scenario. An Ensenso N10 3D camera directly at the "head" of the robot provides the required image data.

Robotic - Ensenso N

High-efficient robotic cell with Ensenso stereo 3D camera

The perfect complement

Globalization is speeding up product comparisons and supply cycles. The days when industrial components could easily be sold "over the counter" are gone. In the robotics market, smaller manufacturers can only prevail over market leaders in the long term through high technical competence and innovation in niche segments. A 3D image processing solution in combination with 6-axis robotics also opens up new opportunities for small and medium-sized companies to establish themselves on the market. ALG Automatisierungslösungen GmbH, headquartered in Baden near Vienna, uses this combination for its applications - for example in a bin picking robotic cell with an integrated Ensenso 3D camera.

Sport - USB 3 LE

Bikefitting system with IDS camera leads professional athletes to success

Success in the saddle

In professional cycling, the avoidance of injuries plays an important role alongside the pursuit of increased performance. Excessive repetitive pedal movement and incorrect posture on the bike can cause functional and biomechanical dysfunctions that lead to pain and worse performance. The French company AR-Entraînement has developed a bike-fitting analysis system based on the assessment of the specific performance requirements and physical abilities and conditions of individual cyclists. In this system a UI-3240LE camera with USB 3.0 interface from IDS detects the movement of the athlete.

Automotive - Ensenso N

Automatic visual inspection system for die cast parts for the automotive industry

Defect-free cast components

Die cast parts made of aluminium and magnesium alloys are increasingly being used in the automotive industry since they ensure a considerable reduction in vehicle weight. Zero-defect quality at the lowest possible cost is an essential requirement for the cast components. Automation is therefore the magic word, especially in the areas of production and processing. A system from VisionTools Bildanalyse Systeme GmbH, Germany, with integrated image processing uses an Ensenso 3D camera to record the geometry of each individual cast component and check its condition and completeness.

Material Analysis - USB 3 uEye ML

Automatic quality control in car body construction in real time

Defects in focus

In the automotive industry, bonding has become a key technology that is increasingly replacing other joining technologies. Both engine and body parts are bonded, and for good reason: bonded cars generally perform better in crash tests than welded cars - provided the quality of the components and bonded areas is flawless. Modern adhesive systems have thus become a safety factor in the automotive industry. For manufacturers, the reliability of the quality control of industrial parts of all kinds is crucial, because defective parts due to non-conformity have serious effects on production performance.