Found in Robotics News & Content, with a score of 10.28
…or has a few years before it’s more than just PR efforts. No one is sure if AI and neural networks will allow some distribution centers to find brand-new ways of pre-staging goods to meet demands or if customers will adopt local lockers and pick-up locations en masse. The future is uncertain and exciting. What we do see as necessary for growing in that future is the ability for the supply chain, and every company in it, to adapt and flex to meet changes in customer and client demands.
Found in Robotics News & Content, with a score of 10.96
…Jetson product line and cutting-edge AI, such as deep neural networks, it becomes possible to structure the information so as to extract troves of useful features,” says Carlos Asmat, lead robotics engineer at Piaggio Fast Forward. “Given the increasing abundance of computational power, it becomes more advantageous to use sensors that can capture as much information as possible while remaining affordable.” Despite these advances, sensing technologies currently supporting smart home robots represent an early, transitional stage of development. Designers and users alike can expect steady change in this sector. “As technology matures, we can add more and more senses to…
Found in Robotics News & Content, with a score of 21.69
…of gathering the right provable data for training the neural net, as the foundation for helping your AI model predict or seek the right data. Think of it as establishing and understanding the gold standard for your project. At a Glance: MathWorks Release 2019b MATLAB and Simulink extended with many new features. New tools for creating or updating Robot Operating System code. Interactively explore and preprocess data with MATLAB Live Editor. Develop, text and deploy 3D simulated driving algorithms. Deep Learning Toolbox extended with new enhancements. Learn more here. Smart products generally have the internal equivalent of a network architecture…
Found in Robotics News & Content, with a score of 18.62
…supported, and Jetson Nano is capable of running multiple neural networks in parallel to process data and drive action. Each SparkFun JetBot AI Kit includes the following: NVIDIA Jetson Nano Developer Kit; Robot Platform Chassis and all Prototyping Electronics; 64GB MicroSD card—pre-flashed with the JetBot Image; 145 Field of View, wide-angle camera module; Wi-Fi adapter; serial controlled motor driver; and micro OLED Breakout. SparkFun is accommodating individuals who already own a Jetson Nano Developer Kit by also releasing a version of the JetBot Kit without one. If people are looking to get started with AI but don’t know how, an…
Found in Robotics News & Content, with a score of 19.15
…together. Over the past decade, innovative applications of deep neural networks coupled with increasing computational power have led to continuous AI breakthroughs in areas such as vision, speech, language processing, translation, robotic control, and even gaming. Advances in AI Capabilities In a recent Microsoft blog, the author describes how each year since 2012, the world has seen a new step function advance in AI capabilities. Though these advances are across very different fields like vision (2012), simple video games (2013), machine translation (2014), complex board games (2015), speech synthesis (2016), image generation (2017), robotic control (2018), and writing text (2019),…
Found in Robotics News & Content, with a score of 24.75
…This is 3YOURMIND’s vision for Agile Manufacturing. More specifically, 3YOURMIND will use the Pro FIT funding to add artificial neural networks (ANNs) into their software. “Our software makes it simple and cost effective for companies to enter and scale additive manufacturin,” says Stephan Kühr, CEO, 3YOURMIND. “By adding more machine learning to our software we will multiply the effectiveness of AM programs. 3YOURMIND is developing the software infrastructure for a level of automation we call agile manufacturing; the ability to quickly and accurately adapt production to customer needs and company resources.“ Sources: Press materials received from the company and additional…
Found in Robotics News & Content, with a score of 11.93
…research term published a paper, “An Intelligent Hybrid Artificial Neural Network-Based Approach for Control of Aerial Robots,” in the Journal of Intelligent & Robotic Systems. It outlines a proposed hybrid control approach that would use AI to enhance the controller so that these autonomous drones could better respond to emergency situations. Kayacan says this hybrid model will benefit from the use of simulation and AI. “This is an enhancement to the navigation and other algorithms,” he says. “We know something about the system, but there are some alternatives. Why don’t I collect more data and train the network in order…
Found in Robotics News & Content, with a score of 10.16
…incorporating surround sensors and AI software running on deep neural networks to protect the driver and the passengers in the car,” says Danny Shapiro, senior director of automotive, NVIDIA. “The technology also includes driver monitoring, and can issue alerts or take action if the driver is distracted or drowsy.” At the NVIDIA GPU Technology Conference (GTC) in March, NVIDIA announced its autonomous car simulation platform NVIDIA DRIVE Constellation is now available. It is a data center solution comprised of two side-by-side servers. The DRIVE Constellation Simulator server uses NVIDIA GPUs running DRIVE Sim software to generate the sensor output from…
Found in Robotics News & Content, with a score of 24.64
…the development agreement, the companies will create an “interconnected network of computer vision and AI algorithms to significantly increase multi-tool and multi-material 3D printing automation.” The companies will also combine an array of high-performance cameras with custom hardware for new robotics capabilities, including real-time in-situ print monitoring with “dynamic intelligent response for parameter adjustment and error correction,” automatic performance of post-processing treatments, object recognition and manipulation, automation of multi-tool hybrid manufacturing processes, and a new user interface. Aether will develop software to automate image processing for P&G, and deep learning techniques will be used to train multiple neural networks to…
Found in Robotics News & Content, with a score of 18.27
…an iterative, three-layered process, built on a hierarchy of neural networks. In the first layer, the system receives input data from sensors and then passes it on to what are called “hidden layers.” In the second tier, the computer performs a succession of computations on the inputs, interpreting sensory data through machine-perception algorithms. Each hidden layer trains on a distinct set of features, based on the previous layer’s output. During this process, the algorithms label and cluster raw input according to similarities among the example inputs. They then classify data when they have a labeled dataset to train with. The…
Found in Robotics News & Content, with a score of 24.80
…various ways. The algorithms use mathematical models in a neural network to identify patterns in data and respond to them. This can be applied for pattern recognition in images, videos, sounds, text and any other type of data. In design, integrating deep learning and design processes can help bring better products to market more quickly. “Deep learning and design engineering can learn a lot from each other and generate surprising outcomes.” — Leslie Nooteboom, Humanising Autonomy Design tools can be applied to deep learning processes to help gather and annotate data, and develop real-world applications, according to Leslie Nooteboom, CDO…
Found in Robotics News & Content, with a score of 8.23
…technologies such as sensors, artificial intelligence and inventory and network optimization. In 2017, the Massachusetts Institute of Technology tested drone technology using RFID tagged items. Drones could read RFID tags tens of meters away with an average error of only 19 centimeters - quite accurate given the distance. Researchers said the goal was to prevent inventory mismatches and locate individual items. “If you're carrying inventory you have inventory accuracy problems and it doesn't matter what line of business you're in, everybody has this problem,” Matt Yearling, CEO of PINC, told Supply Chain Dive. However, automated warehouse inventory systems like drones…