3D Sensing for Logistics Advancements in machine vision are among the key factors that shape automation trends in logistics. One of such advancements is the new machine vision capability to capture fast-moving objects in high quality. This task was not possible to do until recently as one could either get fast scanning speed OR high quality of 3D data - meaning that if a robot was to precisely recognize and handle moving objects, it needed to stop moving for each scan acquisition. This has changed with a novel 3D sensing approach that enables the capture of dynamic scenes in high resolution and accuracy and without motion artifacts. Allowing robots to handle fast-moving objects without interruption shakes up logistics automation by enabling new tasks such as the recognition, picking, and sorting of objects moving on a conveyor belt or on an overhead conveyor, palletization, and depalletization, the dimensioning of objects, their volume measurement, bounding box estimation, or counting, and an infinite number of other applications - all while in motion. Key Technologies: area scan, 3D sensing, sorting, picking, palletization, depalletization Smart Cameras Industrial smart cameras are adding capabilities, such as 3D vision and advanced onboard analytics while cutting weight and size. As a result, they’re moving onto robots and enabling complex assembly, surface finishing, intricate inspections, and other robotic applications. But challenges remain, such as dealing with transparent objects or items in see-through bags and hardening cameras to stay calibrated in 3D while on a plant floor. Key Technologies: 3D Imaging Vision-Guided Robotics Multiple, distinct imaging modalities can be paired with robotic arm systems to perform tasks in both warehousing and logistics environments. To select the optimal imaging technique and the corresponding imaging device, end users must consider the nature of their application. This article looks at three imaging techniques that are widely incorporated/deployed in automated systems to provide vision guidance: structured light-based imaging, time of flight imaging, and ambient stereo imaging. The article introduces advances to each technology, considering the perspectives of camera developers as well as system integrators, to inform on best-use cases for each technique in settings in which related applications necessitate different imaging methods. Key Technologies: Stereo vision, 3D vision AI for Visual Inspection Ensuring Quality with AI for Visual Inspection. This article will discuss how new visual inspection systems, AI apps, and advances in no-code algorithm development and training are bringing automated decision support to manual visual inspection and assembly tasks. In particular, the article will focus on how two manufacturers – a distillery and an electronics manufacturer – are using these tools in their operations. It will discuss how the distillery uses AI tools for in-process operator assistance during manual labeling, and is now adapting the technology as a tool to help provide a final quality control check on products before they are shipped. In the case of the electronics manufacturer, the article will highlight how the company uses AI decision-support alongside more traditional machine vision inspection and why collecting data from manual processes is important. Key Technologies: Visual inspection, AI See Pricing hbspt.forms.create({ region: "na1", portalId: "4478512", formId: "84b5d99c-e78c-4224-88dd-5ae183709a73" });