The Ensenso C addresses current challenges in the automation and robotics industry. Compared to other Ensenso models, it provides both 3D and RGB color information. Customers thus benefit from even more meaningful image data. The housing of the robust 3D camera system meets the requirements of protection class IP65/67. It offers a resolution of 5 MP and is available with baselines from current to approximately 455 mm. This means that even large objects can be reliably detected. The camera is quick and easy to use, and addresses primarily large-volume applications, e.g., in medical technology, logistics, or factory automation.
Up to now, employees have been responsible for loading the containers. This simple subtask is more complex than one might think at first glance. In addition to the actual insertion process, the first step is to determine the appropriate free space for the part. At the same time, any interfering factors, such as interlocks, must be removed, and a general check of the “load box” for any defects must be carried out. All these tasks are to be taken over by a robot with a vision system—a technological challenge. This is because the containers also come from different manufacturers, are of different types, and may sometimes vary in their dimensions.
The main result of the image processing solution is the multivector correction. In this way, the robot is adjusted to be able to insert the component at the next possible, suitable deposit position. Secondary results are error messages due to interfering edges or objects in the container that would prevent filling. Damaged containers that are in a generally poor condition can be detected and sorted out with applied data. The entire image processing takes place in the image processing software MSS (multisensor systems) developed by VMT. FrameSense is designed to be easy to use and can also be converted to other components directly onsite.
Finally, the overall picture is compared with a stored reference model. In this way, the containers can be simultaneously checked for their condition and position in a fully automated manner. Even deformed or slanted containers can be processed. All this information is also recorded for use in a quality management system where the condition of all containers can be traced. The calibration as well as the consolidation of the measurement data and their subsequent evaluation are carried out in a separate IPC (industrial computer) with screen visualization, operating elements, and connection to the respective robot control.
For their fully automatic loading and unloading, the position of several relevant features of the containers must be determined for a so-called multivector correction of the robot. The basis is a type, shape, and position check of the respective container. This is the only way to ensure process-reliable and collision-free path guidance of the loading robot. All this must be integrated into the existing production process. Time delays must be eliminated, and the positioning of the components must be accurate to the millimeter.
Innovation
Automatic Handling of Pressed Parts Through 3D Container Inspection
Four eyes see better than two
Type, shape, and position inspection with the aid of four 3D cameras
Robust 3D camera system
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To achieve this, VMT uses four 3D cameras per system. The four sensors each record a part of the entire image field. This can consist of two containers, each measuring approximately 1.5 m x 2 m x 1.5 m (D x W x H). Two of the cameras focus on one container. This results in data from two perspectives each, to optimize the information quality of the 3D point cloud. The point clouds of all four sensors are combined for the subsequent evaluation. During the process, registrations of relevant features of the container take place in ROIs (regions of interest) of the total point cloud. A registration is the exact positioning of a feature using a model in all six degrees of freedom. In other ROIs, interference contours are searched for that could lead to collisions during loading.
Published: Wednesday, October 18, 2023 – 12:02