Robust and Flexible Robotic Automation in Logistics

Enabling robots to pick unknown objects in harsh logistics environments

Published: Tuesday, March 9, 2021 - 12:03

The global pandemic has radically impacted the supply chain and logistics industry, making the need for robotic automation more urgent than ever. With more than 70 percent of labor in warehousing now dedicated to picking and packing, numerous companies are gradually investing in logistics automation. But what happens when robots must handle an unlimited number of (unknown) stock-keeping units (SKUs)? These companies need a fast, reliable, and robust way to automate picking and placing a large variety of objects.

This challenge was taken up successfully by the Dutch company Fizyr. The computer vision company based in Delft focuses on enabling robots to pick unknown objects even in harsh logistics environments. The result is an automated vision solution that enables logistic automation in various conditions and applications, like item picking, parcel handling, depalletizing, truck unloading, or baggage handling. To complete the system with the optimal hardware, Fizyr integrates compact, robust Ensenso 3D cameras in combination with high-performance GigE uEye cameras from IDS.

Instead of providing a proprietary picking cell, like most players in the market do, Fizyr has created a plug-and-play modular software product that integrates smoothly with any system, giving integrators the freedom to choose the best hardware (e.g., cobots or industrial robots) for their picking cell. While facilitating cost, robustness, and speed optimization, IDS is the preferred partner in terms of cameras. In essence, the camera sees products to be picked or classified. Depending on the individual customer application, up to four Ensenso 3D cameras in combination with GigE uEye CMOS cameras are used.

Ensenso 3D camera allows robots individual handling of unknown objects

The integrated IDS industrial cameras ensure the reliable, precise image capture needed for Fizyr’s software algorithms, which provide more than 100 grasp poses each second, including the classification to handle objects differently. The software also performs quality controls and detects defects to prevent damaged items from being placed on a sorter—with the help of IDS cameras functioning as the eyes of the automatic system.

Thus, these algorithms are able to provide all relevant information about segmentation as well as classification of type of parcel (including box, bag, envelope/flat, tube, cylinder, deformable). The system recognizes outliers or nonconveyables (e.g., damaged goods), best possible grasp poses in six degrees of freedom (6 DoF), and multiple ordered poses per object. It allows sensors or robots to deal with closely stacked or overlapping objects, highly reflective items and apparel in polybags, white-on-white and black-on-black flats, as well as transparent objects.

Because the stereo-vision quality directly depends on the scene’s light condition and object surface textures, finding and calculating coordinates of corresponding points on less textured or reflecting surfaces is very difficult. To meet these high requirements, Fizyrs first choice for customer solutions are camera models out of the IDS portfolio. The uEye GigE CP camera takes 2D images of objects and provides them as input for Fizyr’s algorithms, which then proceed to classify the objects under the camera. The objects can be unknown and varying in shape, size, color, material, and stacking. Then the Ensenso camera creates the point cloud maps, and Fizyr’s software combines it with the information from the 2D image, analyzing the surface of the cloud for suitable grasp poses for the gripper (or multiple grippers), and proposes the best ones. A clear representation of surfaces for different materials is critical because it is a key component of the software’s algorithms. Ensenso 3D cameras from IDS improve the classic stereo vision principle with additional techniques to achieve a higher-quality depth of information and more precise measurement results.

The system robustly segments unknown parcels, even under harsh lighting conditions.

The specific camera models, as well as the number of cameras per system, depend on the individual use case of the customer. For a typical bin-picking solution with a cobot, one Ensenso N35 is used in combination with a GigE uEye CP, but there are clients that use one Ensenso X36 and a GigE uEye CP for bin picking together with four Ensenso N35 cameras for stowing the item in other bins.

The recommended uEye CP stands for “compact power” and is the tiny powerhouse for industrial applications of all kinds. It offers maximum functionality with extensive pixel preprocessing and, thanks to the internal 120 MB image memory, is also perfectly suited for multicamera systems. The camera delivers data at full GigE speed and enables single-cable operation up to 100 m via PoE (power over ethernet).

The selected UI-5240CP-C-HQ Rev. 2 is a particularly powerful industrial camera with the e2v 1.3 megapixel CMOS sensor. This is one of the most sensitive sensors in the IDS product portfolio and is available in a color version as well as monochrome and NIR. Besides its outstanding sensitivity to light, the camera also has a range of other distinctive features that make the sensor extremely flexible if requirements or ambient conditions change.

The compact and robust aluminum housing of the Ensenso N35 3D camera with lockable GPIO connector for trigger and flash, as well as a GigE connector, has two monochrome CMOS sensors (Global Shutter, 1,280 x 1,024 pixels) and a projector. Via PoE, data transfer and power supply are possible with long cable lengths. Due to the integrated FlexView technology, the N35 models are particularly suitable for 3D acquisition of still objects and for working distances up to 3,000 mm.

The Ensenso X36 3D camera system consists of a projector unit; two GigE uEye cameras, either with 1.3 MP or 5 MP sensors (CMOS, monochrome); mounting brackets and adjustment angles; three lenses; and sync-and-patch cables to connect the camera with the projector unit. The FlexView technology ensures a better spatial resolution as well as a high robustness capability for dark or reflecting surfaces.

“Fizyr normally uses one camera per system, usually uEye cameras in combination with Ensenso N35 and X36, but there are no limitations,” says Herbert ten Have, CEO at Fizyr. “The most common use case for Fizyr so far is one uEye and one Ensenso per system.”

The different Ensenso models that can be used have one thing in common: The light-intensive projector produces a high-contrast texture on the object surface by using a pattern mask, even under difficult light conditions. The projected texture supplements the weak or nonexistent object surface structure. Therefore, this principle is also called “projected texture stereo vision.” The result is a more detailed disparity map, and a more complete and homogeneous depth information of the scene.

Packages are localized and classified using 3D image data

Their extensive features qualify both Ensenso 3D camera models for the wide range of demanding applications in the supply chain and logistics industry, such as 3D object recognition, classification, and localization (e.g., quality assurance and commissioning), logistics automation (e.g., palletizing and depalltizing), robot applications (e.g., bin picking), capturing objects up to 8 cubic meters, (e.g., pallets), or automatic storage systems.

“Fizyr has integrated the Ensenso SDK in its software using a modern and fast wrapper,” ten Have explains. “A great advantage is the 2D/3D combination, which allows the image from the 2D camera to be placed over the 3D point cloud as an overlay.” This provides a more vivid impression of the scene. On the other hand, the camera image can be optimally adjusted to the robot coordinate system by means of “hand-eye calibration” in order to ensure a target-oriented gripping.

Outlook

The strong growth of e-commerce has increased the demand for larger packages. At the same time, the constraints imposed by the global pandemic have led both to a reduction in the available labor force and an urgent need for physical distance in companies. To meet these challenges, companies are increasingly turning to robotic automation, in which artificial intelligence and machine vision play a crucial role. At the same time, this reduces costs and increases occupational safety.

The demand for high-quality modules for state-of-the-art automated picking cells is growing worldwide. System integrators’ requirements for software and hardware components are increasing in equal measure. The Fizyr-IDS solution offers the following advantages:
• As a plug-and-play solution, it enables easy integration into any system.
• It is hardware-agnostic and thus enables customers to flexibly adapt their order-picking system to their needs at any time.
• It includes a robust, precise, flexible, and easy-to-use 3D vision system that provides optimal object information at all times.

All of them are indispensable components of a future-proof automated “good-to-person” system.

About The Author

Silke von Gemmingen

Silke von Gemmingen manages corporate communications for German camera manufacturer IDS Imaging Development Systems.