An autonomous drone carrying water to help extinguish a wildfire in the Sierra Nevada might encounter swirling Santa Ana winds that threaten to push it off course. Rapidly adapting to these unknown disturbances inflight presents an enormous challenge for the drone’s flight control system.
To help such a drone stay on target, MIT researchers developed a new, machine learning-based adaptive control algorithm that could minimize its deviation from its intended trajectory in the face of unpredictable forces like gusty winds.
The study is published on the arXiv preprint server.
Unmanned Aerial Vehicle (UAV) deployment has risen rapidly in recent years. They are now used in a wide range of applications, from critical safety-of-life scenarios like nuclear power plant surveillance to entertainment and hobby applications…
The world’s largest drone “mothership” is getting ready for deployment in June. It’s designed to carry and launch up to 100 drones in a swarm, including kamikaze drones.
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An Asinoid can power a fleet of autonomous drones. Act as the brain inside your security system. It can drive your R&D, run your meetings, become the cognitive layer behind your SaaS product or even co-found a company with you.
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As demand surges for batteries that store more energy and last longer—powering electric vehicles, drones, and energy storage systems—a team of South Korean researchers has introduced an approach to overcome a major limitation of conventional lithium-ion batteries (LIBs): unstable interfaces between electrodes and electrolytes.
Most of today’s consumer electronics—such as smartphones and laptops—rely on graphite-based batteries. While graphite offers long-term stability, it falls short in energy capacity.
Silicon, by contrast, can store nearly 10 times more lithium ions, making it a promising next-generation anode material. However, silicon’s main drawback is its dramatic volume expansion and contraction during charge and discharge, swelling up to three times its original size.
A research team has developed a high-performance supercapacitor that is expected to become the next generation of energy storage devices. With details published in the journal Composites Part B: Engineering, the technology developed by the researchers overcomes the limitations of existing supercapacitors by utilizing an innovative fiber structure composed of single-walled carbon nanotubes (CNTs) and the conductive polymer polyaniline (PANI).
Compared to conventional batteries, supercapacitors offer faster charging and higher power density, with less degradation over tens of thousands of charge and discharge cycles. However, their relatively low energy density limits their use over long periods of time, which has limited their use in practical applications such as electric vehicles and drones.
Researchers led by Dr. Bon-Cheol Ku and Dr. Seo Gyun Kim of the Carbon Composite Materials Research Center at the Korea Institute of Science and Technology (KIST) and Professor Yuanzhe Piao of Seoul National University (SNU), uniformly chemically bonded single-walled carbon nanotubes (CNTs), which are highly conductive, with polyaniline (PANI), which is processable and inexpensive, at the nanoscale.
