Found in Robotics News & Content, with a score of 14.64
…CPU and the 4.6 TOPS (trillion operations per second) neural processor unit (NPU) in the eCV1 chip, which provides dedicated machine learning instructions, a patented neural network engine, and Tensor Processing Fabric Flexible image and computer vision processing for domain-specific applications The new platform also supplies developers with H.264 compression for easy video streaming, said the company. XINK's Crypto Engine includes ARM's TrustZone for security, as well as a pseudo-random number generator and other encryption to protect user data through hardware-based isolation. eYs3D exhibits at CES 2023 eYs3D Microelectronics demonstrated the XINK development framework at CES Booth 15769 in the…
Found in Robotics News & Content, with a score of 14.35
…backed by the company’s dedicated service and support teams. Neural network recognizes billions of containers AMP added that its neural network has recognized more than 75 billion containers and packaging types in real-world conditions annually. AMP Vision is a modular computer vision system that helps operators understand material flow throughout key stages of sorting operations. When integrated with AMP Clarity, the company’s portal for recycling data and insights and robot optimization, customers can use AMP Vision to monitor real-time material characterization and performance measurement throughout a facility. AMP Vortex is designed to tackle film contamination and improve recovery of film…
Found in Robotics News & Content, with a score of 14.22
…enable automatic target recognition. In addition, AO’s ensemble deep-learning neural networks power sonar-data analysis. They empower predictions that are more accurate than those of individual models, claimed Terradepth. Platform users can display seafloor objects within respective interest regions. “Our ocean data-as-a-service model will leverage our browser-based, cloud infrastructure to make accessible valuable and mission-critical data in a secure manner to internal stakeholders, as well as interested third parties,” Martzial said. “Our ODaaS platform will be able to provide on-demand ocean data access to enterprise business units, departments or customers, regardless of geography.” Terradepth AO supports decision making Terradepth said Absolute…
Found in Robotics News & Content, with a score of 14.19
…modularity, claimed the company. They are powered by robust neural networks that were trained on thousands of items to be able to recognize boxes and goods of various shapes, sizes, colors, materials, and textures, said Photoneo. “The [Depalletization] algorithms can also easily recognize boxes that are very tightly packed,” said Pufflerova. “This is often a big challenge for automation systems, as it is difficult for them to differentiate the line separating two boxes from a line contouring the opening of one particular box.” “The modular nature of Depalletization allows you to use the tool as a stand-alone vision solution or…
Found in Robotics News & Content, with a score of 14.09
…We've transitioned from a hybrid approach relying more on neural networks to understand the scene and types of packages and make better decisions on how to pick them and how to orient end effectors. Certain suction cups have better properties for picking loose polybags, and the system knows where to place it and the overall order of picking. For the multi-pick end effector, what size or sorts of items are most commonly fulfilled? How does its throughput compare with current industry norms? Georgiev: Our end effector ranges from small envelopes of 3x3 in. flat to bigger boxes of 20x20x20 in.…
Found in Robotics News & Content, with a score of 14.00
…on a transformer deep learning architecture that allows a neural network to learn by tracking relationships in data. They’re generally trained on huge datasets and can be used to process and understand sensor and robot information as magically as ChatGPT for text. This enables robot perception and decision-making like never before and provides zero-shot learning - the ability to perform tasks without prior examples. NVIDIA’s collaboration with Intrinsic, a robotics software and AI company, demonstrates the potential for a universally applicable robotic-grasping skill to work across grippers, environments and objects. “For the broader industry, our work with NVIDIA shows how…
Found in Robotics News & Content, with a score of 13.61
…avoid possible collisions in traffic. Clevon uses multiple deep neural networks, fusing camera and radar data to allow its vehicles to detect and identify the dynamic environment. It said its technical team in Estonia is constantly developing and improving the CLEVON 1, so one teleoperator could eventually manage five to 10 vehicles simultaneously. The CLEVON 1 communicates via 4G with the operator in the control room and includes redunandcies for safety. “Reliable data connectivity is crucial for this technology,” explained Vancauwenberghe. “To be sure, the vehicle has two SIM cards from two different providers, so there is always a network…
Found in Robotics News & Content, with a score of 13.42
…(SoCs) offer high-resolution video compression, image processing, and deep neural network processing to enable cameras to extract valuable data from video streams. Oculii applies AI to radar “For decades, commercial radars have suffered from poor angular resolution and limited FOVs [fields of view] because traditional designs require more antennas for higher resolution,” said Dayton, Ohio-based Oculii. “Additional antennas increase cost, size, and power exponentially, limiting what is commercially feasible.” Founded in 2015, the company claimed that the adaptive AI algorithms in its Virtual Aperture Imaging technology use current radar chips to achieve up to 100 times greater resolution, improved accuracy,…
Found in Robotics News & Content, with a score of 12.82
…It describes the DeepSeeColor model, which uses two convolutional neural networks to reduce backscatter and correct colors in real time on the NVIDIA Jetson Orin NX while undersea. “NVIDIA GPUs are involved in a large portion of our pipeline because, basically, when the images come in, we use DeepSeeColor to color correct them, and then we can do the fish detection and transmit that to a scientist up at the surface on a boat,” said Stewart Jamieson, a robotics Ph.D. candidate at MIT and an AI developer at WARPLab. CUREE cameras detect fish and reefs CUREE includes four forward-facing cameras,…
Found in Robotics News & Content, with a score of 12.53
…the ideal balance between computational speed and accuracy. The neural network autonomously recognizes the surfaces from which an object can be picked, using a suction cup to facilitate identification of the most suitable grasping points. As a result, MI.RA/OnePicker can achieve path planning and collision-free movements safely while ensuring optimal piece picking performance by the robot, Comau said. The vision-based piece picking system can autonomously grasp randomly-placed heterogeneous objects As an all-in-one-system, MI.RA/OnePicker comes with Comau’s Racer5 cobot, a six-axis articulated robot that the company said can deliver speed, accuracy, repeatability, and certified fenceless collaboration safety without cages. The compact…
Found in Robotics News & Content, with a score of 12.28
…physics principles rather than taking noisy data. Our deep neural networks use insect-like vision to create structured 3D geometry. We're looking for AI intelligent animals versus Web-based robotics.” Electric Sheep grows through acquisition The acquisitions of Phenix Landscape and Complete Landscape will help Electric Sheep to grow eightfold, predicted the company. It plans to offer full services including data collection rather than just robotics as a service (RaaS), asserted Murthy. “This gets to the heart of why we chose this business model,” he told Robotics 24/7. “There's an inability to unlock value from progressive automation, which is held to extremely…
Found in Robotics News & Content, with a score of 11.99
…CAD In May 16, 2018, explaining how Google uses neural networks to speed up Gmail users’ email composition in a blog post, Yonghui Wu, Principal Engineer of the Google Brain Team, wrote, “Smart Compose is a new feature in Gmail that uses machine learning to interactively offer sentence completion suggestions as you type, allowing you to draft emails faster. Building upon technology developed for Smart Reply, Smart Compose offers a new way to help you compose messages—whether you are responding to an incoming email or drafting a new one from scratch.” Similar types of R&D efforts are ongoing in the…