Video Friday is your weekly selection of awesome robotics videos, collected by your friends at IEEE Spectrum robotics. We also post a weekly calendar of upcoming robotics events for the next few months. Please send us your events for inclusion.
Cybathlon Challenges: 2 February 2024, ZURICH ICRA 2024: 13–17 May 2024, YOKOHAMA, JAPAN
Enjoy today’s videos!
Researchers used a rubbery polymer to make a new electrolyte membrane that is less likely to crack and lasts 1.7 times longer than before.
BYD’s announcement of a substantial upgrade to its intelligent driving system signals a notable advancement in its efforts to improve this technology. Scheduled for March 30th, this update signifies a significant step forward for BYD in the realm of advanced driver assistance systems (ADAS). The upgrade will further enhance its Navigation On Autopilot (NOA) or its internally known Urban Navigation Assistance (UNA) system in cities across China.
The upgrade was alluded to in 2023 with the BYD Denza N7 with its advanced lidar system and came on the heels of recent improvements to Xpeng’s XNGP intelligent driving system. Telsa has also been a strong competitor in the intelligent driving race, with announcements last year aiming to improve its FSD system. According to sources, the initial rollout of BYD’s Urban Navigation Assistance (UNA) system is slated for March 30th, starting with the N7 model among its existing lineup of over 20 vehicles.
A coating that can hide objects in plain sight, or an implant that behaves exactly like bone tissue—these extraordinary objects are already made from “metamaterials.” Researchers from TU Delft have now developed an AI tool that not only can discover such extraordinary materials but also makes them fabrication-ready and durable. This makes it possible to create devices with unprecedented functionalities. They have published their findings in Advanced Materials.
The properties of normal materials, such as stiffness and flexibility, are determined by the molecular composition of the material, but the properties of metamaterials are determined by the geometry of the structure from which they are built. Researchers design these structures digitally and then have it 3D-printed. The resulting metamaterials can exhibit unnatural and extreme properties. Researchers have, for instance, designed metamaterials that, despite being solid, behave like a fluid.
Continue reading “New AI tool discovers realistic ‘metamaterials’ with unusual properties” »
ScrubMarine, a pioneering marine sector startup, is diving headfirst into the inaugural cohort of Heriot-Watt University’s DeepTech LaunchPad. The company, led by engineer Clyne Albertelli, is making waves with its underwater robot designed to combat biofouling—a persistent challenge for the shipping industry.
Biofouling is the accumulation of microorganisms, plants, and algae on marine vessels. It poses significant threats to hull structures and propulsion systems.
ScrubMarine’s autonomous underwater robot is on a mission to scrub away these challenges, promising to cut fuel costs, reduce maintenance needs, and minimize environmental impact for ships, boats, and submarines.
A coating that can hide objects in plain sight, or an implant that behaves exactly like bone tissue. These extraordinary objects are already made from metamaterials. Researchers from TU Delft have now developed an AI tool that not only can discover such extraordinary materials but also makes them fabrication-ready and durable. This makes it possible to create devices with unprecedented functionalities.
They published their findings in Advanced Materials (“Deep Learning for Size-Agnostic Inverse Design of Random-Network 3D Printed Mechanical Metamaterials”).
Continue reading “New AI tool discovers realistic metamaterials with unusual properties (w/video)” »
Microsoft is back with another Super Bowl ad, this time for its AI chatbot called Copilot. And it kind of sucks.
SingularityNET’s community leaders reflect back on last year’s progress, ecosystem updates, as well as the massive push towards building beneficial AGI in 2024 and beyond.
Register for our BGI Summit today by visiting: https://bgi24.ai.
Continue reading “SingularityNET’s Big AGI Plans for 2024” »
Reliable quantum gates are the fundamental component of quantum information processing. However, achieving high-dimensional unitary transformations in a scalable and compact manner with ultrahigh fidelities remains a great challenge.
To address this issue, scientists in China showcase the use of deep diffractive neural networks (D2NNs) to construct a series of high-dimensional quantum gates, which are encoded by the spatial modes of photons. This work, published in Light: Science & Applications, offers a new paradigm for quantum gate design using deep learning.
Quantum computing holds the promise of transforming our information processing methodologies, and at its core, reliable quantum logic gates play an essential role in quantum information processing.
Wavelength-selective thermal emitters (WS-TEs) have been frequently designed to achieve desired target emissivity spectra, as in typical emissivity engineering, for broad applications such as thermal camouflage, radiative cooling, and gas sensing, etc.
However, previous designs required prior knowledge of materials or structures for different applications, and the designed WS-TEs usually vary from application to application in terms of materials and structures, thus there is no general design framework for emissivity engineering across different applications. Moreover, previous designs fail to tackle the simultaneous design of both materials and structures, as they either fix materials to design structures or fix structures to select suitable materials.
In a new paper published in Light: Science & Applications, a team of scientists, led by Professor Run Hu from School of Energy and Power Engineering, Huazhong University of Science and Technology, China, and coworkers have proposed a general deep learning framework based on the deep Q-learning network algorithm (DQN) for efficient optimal design of WS-TEs across different applications.
