[Video Introduction] DOBOT Case Study: Pickup and Alignment of 7mm Parts

We are currently offering a sample of the educational material "Automatic Judgment Control Using Microscopy and Deep Learning" for educational institutions! This material allows practical learning from judgment of work using machine learning with Raspberry Pi 4B, a microscope, and DOBOT Magician, to the construction of a good/bad product judgment and sorting system in collaboration with a robotic arm. If you are interested, please download the PDF from the related catalog below or feel free to contact us. 【Features】 - Learn the processes of machine learning and judgment methods, how to set thresholds, and the differences between classifiers. - Using a microscope allows for the discrimination of subtle differences such as scratches and gloss. - Utilize a conveyor belt to create an environment for learning about smart factories. 【Learning Content】 - Creation of a dataset Capture images of good/bad products. - Learning and inference Use the dataset for training, create a weight data file, and perform inference. Send the results of good/bad to DOBOT based on the inference results. - Control of DOBOT Magician Sorting is performed based on good/bad results.

We will introduce its features in a video along with the actual programming screen and the movements of the DOBOT Magician. For detailed content, please refer to the URL below or related links. https://www.ipros.jp/product/detail/2000618730 ■ What is DOBOT Magician Despite being priced around 150,000 yen, it is a small robotic arm equipped with a 4-axis arm and comes with standard tool heads such as a gripper, suction cup kit, lighting & drawing, and 3D printer. The dedicated software allows programming by arranging blocks, enabling beginners to smoothly learn and operate the robotic arm. The main unit does not require prior safety education, making it easy to install and use in various locations and scenes. Afrel provides original guides (control learning texts) using dedicated software (DobotStudio) and programming languages to support the utilization of the robotic arm. 【DOBOT Magician explanatory article】 https://learninglab.afrel.co.jp/1074/

We have released a video that verifies "How much weight can the small robot arm DOBOT Magician carry?" For more details, please visit the URL below or the related links. https://www.ipros.jp/product/detail/2000619331 ■ What is DOBOT Magician? Despite being priced around 150,000 yen, it is a small robot arm equipped with a 4-axis arm and comes with standard tool heads such as a gripper, suction cup kit, lighting & drawing tools, and a 3D printer. The dedicated software allows programming by arranging blocks, enabling beginners to smoothly learn and operate the robot arm. The device does not require prior safety training, making it easy to install and use in various locations and scenes. Afrel provides original guides (control learning texts) using dedicated software (DobotStudio) and programming languages to support the utilization of the robot arm. 【DOBOT Magician explanatory article】 https://learninglab.afrel.co.jp/1074/

As the global labor force is predicted to decline, the introduction of robots is expanding domestically, regardless of company size, with particular attention being paid to collaborative robots that can work alongside humans. We have compiled the 10 questions that are always asked during consultation sessions for the compact robot arm, DOBOT Magician, which can be installed on a tabletop. If you are interested, please download the PDF from the related catalog below or feel free to contact us. ■Contents - 10 Questions That Are Always Asked Can beginners use it? Is DobotStudio free? Can it be controlled with programming languages? How long does it take to output with a 3D printer? Can a camera be connected for image recognition and image processing? Answers to 5 other questions - Functions and Features - External Expansion (PLC, Analog Sensors, Digital Sensors) - Expansion Products *DOBOT Magician Explanation Article https://learninglab.afrel.co.jp/1074/ *Free Seminar https://learninglab.afrel.co.jp/seminar/13/