Browse Topic: Automation
We present DISRUPT, a research project to develop a cooperative traffic perception and prediction system based on networked infrastructure and vehicle sensors. Decentralized tracking and prediction algorithms are used to estimate the dynamic state of road users and predict their state in the near future. Compared to centralized approaches, which currently dominate traffic perception, decentralized algorithms offer advantages such as greater flexibility, robustness and scalability. Mobile sensor boxes are used as infrastructure sensors and the locally calculated state estimates are communicated in such a way that they can augment local estimates from other sensor boxes and/or vehicles. In addition, the information is transferred to a cloud that collects the local estimates and provides traffic visualization functionalities. The prediction module then calculates the future dynamic state based on neurocognitive behavior models and a measure of a road user's risk of being involved in
Swimming robots play a crucial role in mapping pollution, studying aquatic ecosystems, and monitoring water quality in sensitive areas such as coral reefs or lake shores. However, many devices rely on noisy propellers, which can disturb or harm wildlife. The natural clutter in these environments — including plants, animals, and debris — also poses a challenge to robotic swimmers.
The global medical device manufacturing industry is undergoing a rapid transformation driven by technological innovation, automation, and increasing demands for customized, high-quality care. For engineers at the heart of medtech manufacturing, understanding the latest technologies is crucial not only for maintaining competitiveness but also for ensuring regulatory compliance, improving time to market, and optimizing production workflows.
Low-cost jelly-like materials, developed by researchers at the University of Cambridge, can sense strain, temperature, and humidity. And unlike earlier self-healing robots, they can also partially repair themselves at room temperature.
Repartly, a startup based in Guetersloh, Germany, is using ABB’s collaborative robots to repair and refurbish electronic circuit boards in household appliances. Three GoFa cobots handle the sorting, visual inspection and precise soldering tasks enabling the company to enhance efficiency and maintain high quality standards.
Innovators at NASA Johnson Space Center have developed a robotic system whose primary structural platform, or “orb,” can be injected into a pipe network and perform reconnaissance of piping infrastructure and other interior volumes. When deployed, this technology uses throttled fluid flow from a companion device for passive propulsion. A tethered line facilitates directional control by the orb’s operator, allowing it to navigate through various piping configurations, including 90° junctions.
It’s a game a lot of us played as children — and maybe even later in life: unspooling measuring tape to see how far it would extend before bending. But to engineers at the University of California San Diego, this game was an inspiration, suggesting that measuring tape could become a great material for a robotic gripper.
For the team at SmartCap, building top-notch gear for outdoor adventurers isn’t just a business — it’s a passion driven by their own love for the wild. But as demand for their rugged, modular truck caps soared after their move to North America in 2022, they hit a snag: How do you ramp up production without sacrificing the meticulous quality you are known for, all while navigating a tough labor market? Their answer? A bold step into the world of intelligent automation, teaming up with GrayMatter Robotics, and employing the company’s innovative Scan&Sand™ system.
Researchers have developed a tiny magnetic robot that can take 3D scans from deep within the body and could revolutionize early cancer detection.
A team of UCLA engineers and their colleagues have developed a new design strategy and 3D printing technique to build robots in one single step. The breakthrough enabled the entire mechanical and electronic systems needed to operate a robot to be manufactured all at once by a new type of 3D printing process for engineered active materials with multiple functions (also known as metamaterials). Once 3D printed, a “meta-bot” will be capable of propulsion, movement, sensing, and decision-making.
Engineers have designed robots that crawl, swim, fly, and even slither like a snake, but no robot can hold a candle to a squirrel, which can parkour through a thicket of branches, leap across perilous gaps and execute pinpoint landings on the flimsiest of branches.
When we last heard from MELD Manufacturing, the large-scale 3D printer supplier was taking first place in the Robotics/Automation/Manufacturing category at the 2018 .
Letter from the Guest Editors
Additive manufacturing has been a game-changer in helping to create parts and equipment for the Department of Defense's (DoD's) industrial base. A naval facility in Washington state has become a leader in implementing additive manufacturing and repair technologies using various processes and materials to quickly create much-needed parts for submarines and ships. One of the many industrial buildings at the Naval Undersea Warfare Center Division, Keyport, in Washington, is the Manufacturing, Automation, Repair and Integration Networking Area Center, a large development center housing various additive manufacturing systems.
This document describes machine-to-machine (M2M)1 communication to enable cooperation between two or more traffic participants or CDA devices hosted or controlled by said traffic participants. The cooperation supports or enables performance of the dynamic driving task (DDT) for a subject vehicle equipped with an engaged driving automation system feature and a CDA device. Other participants may include other vehicles with driving automation feature(s) engaged, shared road users (e.g., drivers of conventional vehicles or pedestrians or cyclists carrying compatible personal devices), or compatible road operator devices (e.g., those used by personnel who maintain or operate traffic signals or work zones). Cooperative driving automation (CDA) aims to improve the safety and flow of traffic and/or facilitate road operations by supporting the safer and more efficient movement of multiple vehicles in proximity to one another. This is accomplished, for example, by sharing information that can be
Drone show accidents highlight the challenges of maintaining safety in what engineers call “multiagent systems” — systems of multiple coordinated, collaborative, and computer-programmed agents, such as robots, drones, and self-driving cars.
Los Angeles-based plastics contract manufacturer Kal Plastics deployed UR10e trimming cobot for a fraction of the cost and lead time of a CNC machine, cut trimming time nearly in half, and reduced late shipments to under one percent — all while improving employee safety and growth opportunities.
Advances in artificial intelligence (AI), machine learning (ML), and sensor fusion drive robotics functionality across many applications, including healthcare. Ongoing innovations in high-speed connectivity, edge computing, network redundancy, and fail-safe procedures crucial to optimizing robotics opportunities. The emergence of natural language processing and emotional AI functionality are poised to propel more intuitive, responsive, and adaptive human-machine interaction.
Researchers at Universidad Carlos III de Madrid (UC3M) have developed a new soft joint model for robots with an asymmetrical triangular structure and an extremely thin central column. This breakthrough, recently patented, allows for versatility of movement, adaptability and safety, and will have a major impact in the field of robotics.
While some developers of autonomous technology for commercial trucks have stalled out, there's renewed energy to deliver augmented ADAS and automated driving systems to mass production. After a tumultuous 2023 that saw several autonomous trucking startups pivot out of or exit the arena entirely, there has been a recent resurgence of investment and efforts to bring the vision of driverless freight fleets to reality. In the wake of firms like Embark, TuSimple and Waymo scaling back or rolling up operations, Aurora, Continental and Knorr-Bremse have all announced continued development of SAE Level 4 systems with the intention to deploy trucks using these systems at scale. OEMs such as Volvo Trucks have also announced updates to existing technologies that will augment current advanced driver-assistance systems (ADAS) to help human drivers become safer behind the wheel.
Accurate object pose estimation refers to the ability of a robot to determine both the position and orientation of an object. It is essential for robotics, especially in pick-and-place tasks, which are crucial in industries such as manufacturing and logistics. As robots are increasingly tasked with complex operations, their ability to precisely determine the six degrees of freedom (6D pose) of objects, position, and orientation, becomes critical. This ability ensures that robots can interact with objects in a reliable and safe manner. However, despite advancements in deep learning, the performance of 6D pose estimation algorithms largely depends on the quality of the data they are trained on.
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