Photoneo

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Bratislava, Slovakia

Photoneo is a leading provider of robotic vision and intelligence. Based on a patented 3D technology, Photoneo developed the world’s highest-resolution and highest-accuracy 3D camera, thus unlocking the full potential of powerful, reliable, and fast machine learning and also reducing the training and deployment time. By bringing intelligent robots into the field, Photoneo helps companies mainly in the automotive, logistics, e-commerce, food, and medical industries to improve the performance and efficiency of their manufacturing, fulfillment, and assembly processes.

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Industry 5.0: Adding the Human Edge to Industry 4.0

Date:

Author: Andrew Lightstead

Topics: Industrial Robot, Robot Picking

Organizations: Photoneo

The arms of pick and place robots are equipped with end effectors similar to human hands that are specifically designed for picking various types of objects. These may include components that are further used in the manufacturing processes of products.

Pick and place robots have a wide range of capabilities. Depending on specific application requirements, they can be equipped with several types of end effectors. The most common ones include vacuum grippers with suction cups, fingered grippers, clawed grippers, magnetic grippers, or custom grippers. To achieve a high level of flexibility, pick and place robots are often equipped with multiple arms and heads. This helps them approach objects from several angles at any given time.

Read more at Photoneo Blog

Evaluation Criteria for Trajectories of Robotic Arms

Date:

Topics: Robotic Arm

Organizations: Slovak University of Technology, Photoneo

This paper presents a complex trajectory evaluation framework with a high potential for use in many industrial applications. The framework focuses on the evaluation of robotic arm trajectories containing only robot states defined in joint space without any time parametrization (velocities or accelerations). The solution presented in this article consists of multiple criteria, mainly based on well-known trajectory metrics. These were slightly modified to allow their application to this type of trajectory. Our framework provides the methodology on how to accurately compare paths generated by randomized-based path planners, with respect to the numerous industrial optimization criteria. Therefore, the selection of the optimal path planner or its configuration for specific applications is much easier. The designed criteria were thoroughly experimentally evaluated using a real industrial robot. The results of these experiments confirmed the correlation between the predicted robot behavior and the behavior of the robot during the trajectory execution.

Read more at MDPI

3D Vision Technology Advances to Keep Pace With Bin Picking Challenges

Date:

Author: Jimmy Carroll

Topics: machine vision, convolutional neural network

Organizations: Zivid, CapSen Robotics, IDS Imaging Development Systems, Photoneo, Universal Robots, Allied Moulded

When a bin has one type of object with a fixed shape, bin picking is straightforward, as CAD models can easily recognize and localize individual items. But randomly positioned objects can overlap or become entangled, presenting one of the greatest challenges in bin picking. Identifying objects with varying shapes, sizes, colors, and materials poses an even larger challenge, but by deploying deep learning algorithms, it is possible to find and match objects that do not conform to one single geometrical description but belong to a general class defined by examples, according to Andrea Pufflerova, Public Relations Specialist at Photoneo.

“A well-trained convolutional neural network (CNN) can recognize and classify mixed and new types of objects that it has never come across before,”

Read more at A3