Elon Musk is hailed as an innovator and disrupter who went from knowing next to nothing about building cars to running the world's most valuable automaker in the space of 16 years. But his record shows he is more of a fast learner who forged alliances with firms that had technology Tesla lacked, hired some of their most talented people, and then powered through the boundaries that limited more risk-averse partners. Now, Musk and his team are preparing to outline new steps in Tesla's drive to become a more self-sufficient company less reliant on suppliers at its "Battery Day" event on Tuesday. Musk has been dropping hints for months that significant advances in technology will be announced as Tesla strives to produce the low-cost, long-lasting batteries that could put its electric cars on a more equal footing with cheaper gasoline vehicles. New battery cell designs, chemistries and manufacturing processes are just some of the developments that would allow Tesla to reduce its reliance on its long-time battery partner, Japan's Panasonic, people familiar with the situation said.

Purchases you make through our links may earn us a commission. Our colleague Marc Saltzman from USA TODAY is here to share some insight into how smart robots can help do your housework and make your life easier. Now that society is cautiously opening up ahead of the fall season, the last thing you want to do is more work around the house. Not to mention, you might be busy getting the kids ready for another school year – at home, in class, or a bit of both. Fortunately, technology can help, so you can focus on what matters.

Today's robot-mounted batteries provide electrical power but at the expense of added mass that in turn requires added power to move and use. But a team of researchers from the University of Michigan have devised a clever solution that will enable tomorrow's batteries to provide power while negating their own weight -- it just needs a bit of Kevlar. Led by Nicholas Kotov, a professor of chemical engineering at U of Michigan, the team has developed a battery system that is strong enough to also serve as a structural support for the rest of the robot. "Robot designs are restricted by the need for batteries that often occupy 20% or more of the available space inside a robot, or account for a similar proportion of the robot's weight," Kotov told the University of Michigan News "No other structural battery reported is comparable, in terms of energy density, to today's state-of-the-art advanced lithium batteries. We improved our prior version of structural zinc batteries on 10 different measures, some of which are 100 times better, to make it happen," he continued.

Join the audience for a live webinar at 6 p.m. BST/1 p.m. EST on 12 August 2020 on the discovery of a novel battery electrolyte that was guided by machine-learning software without human intervention Want to take part in this webinar? Innovations in batteries take years to formulate and commercialize, requiring extensive experimentation during the design and optimization phases. We approached the design and selection of a battery electrolyte through a black-box optimization algorithm directly integrated into a robotic test stand. We report here the discovery of a novel battery electrolyte by this experiment completely guided by the machine-learning software without human intervention. Motivated by the recent trend toward super-concentrated aqueous electrolytes for high-performance batteries, we utilize Dragonfly – a Bayesian machine-learning software package – to search mixtures of commonly used lithium and sodium salts for super-concentrated aqueous electrolytes with wide electrochemical stability windows.

Industrial Control Systems (ICS) are used to control physical processes in critical infrastructure. These systems are used in a wide variety of operations such as water treatment, power generation and distribution, and manufacturing. While the safety and security of these systems are of serious concern, recent reports have shown an increase in targeted attacks aimed at manipulating physical processes to cause catastrophic consequences. This trend emphasizes the need for algorithms and tools that provide resilient and smart attack detection mechanisms to protect ICS. In this paper, we propose an anomaly detection framework for ICS based on a deep neural network. The proposed methodology uses dilated convolution and long short-term memory (LSTM) layers to learn temporal as well as long term dependencies within sensor and actuator data in an ICS. The sensor/actuator data are passed through a unique feature engineering pipeline where wavelet transformation is applied to the sensor signals to extract features that are fed into the model. Additionally, this paper explores four variations of supervised deep learning models, as well as an unsupervised support vector machine (SVM) model for this problem. The proposed framework is validated on Secure Water Treatment testbed results. This framework detects more attacks in a shorter period of time than previously published methods.

Matt Carlson is the Vice President of Business Development at WiBotic Inc, a company that provides reliable wireless power solutions to charge aerial, mobile and aquatic robot systems. Why are wireless charging solutions so important to the future of robotics? Robots need the ability to autonomously charge for most applications. It simply isn't cost effective to hire a staff of workers to manage battery charging or battery swapping. However, most autonomous charging today is done using docking stations that require physical mating of electrical contacts.

I'm not sure if Moflin is supposed to be a robotic hamster, guinea pig, baby bunny, or some alternate take on a Tribble, but goddamn this robo-pet is cute. Launched as part of a Kickstarter campaign from Vanguard Industries that went live earlier this week, Moflin looks to follow in the steps of Sony's Aibo or other robo-pets like Qoobo. However, instead of simply a disembodied tail attached to a fluffy base like Qoobo, Moflin apparently uses AI to have "emotional capabilities" meant to more accurately mimic real pets, so that it can express feelings and potentially even serve as a therapeutic aid. In order to make that happen, Vanguard Industries said it created its own Emotion AI tech that allows Moflin's feelings to react and evolve over time based on contact with humans. Individual Moflins can even have unique personalities based on their experiences, and learn to react differently depending on the actions of their owners.

To meet the growing quest for enhanced network capacity, mobile network operators (MNOs) are deploying dense infrastructures of small cells. This, in turn, increases the power consumption of mobile networks, thus impacting the environment. As a result, we have seen a recent trend of powering mobile networks with harvested ambient energy to achieve both environmental and cost benefits. In this paper, we consider a network of virtualized small cells (vSCs) powered by energy harvesters and equipped with rechargeable batteries, which can opportunistically offload baseband (BB) functions to a grid-connected edge server depending on their energy availability. We formulate the corresponding grid energy and traffic drop rate minimization problem, and propose a distributed deep reinforcement learning (DDRL) solution. Coordination among vSCs is enabled via the exchange of battery state information. The evaluation of the network performance in terms of grid energy consumption and traffic drop rate confirms that enabling coordination among the vSCs via knowledge exchange achieves a performance close to the optimal. Numerical results also confirm that the proposed DDRL solution provides higher network performance, better adaptation to the changing environment, and higher cost savings with respect to a tabular multi-agent reinforcement learning (MRL) solution used as a benchmark.

This summer I've been testing several lawn mowers, the most unique of which is this robot from WORX. This is the WORX Landroid M robotic mower, a fully automated, cordless, rechargeable battery powered piece of equipment that'll do all your work for you. The biggest obstacle you'll face is setup, and that's pretty straightforward if you follow the directions step-by-step. The Parts Included in our review is the basic WORX Landroid M robotic mower and a few add-ons. If you're looking at the WORX website (or WORX in a store) there are at least two versions of this Landroid M, one with GPS, one without.

AI techniques are being applied by researchers aiming to extend the life and monitor the health of batteries, with the aim of powering the next generation of electric vehicles and consumer electronics. Researchers at Cambridge and Newcastle Universities have designed a machine learning method that can predict battery health with ten times the accuracy of the current industry standard, according to an account in ScienceDaily. The promise is to develop safer and more reliable batteries. In a new way to monitor batteries, the researchers sent electrical pulses into them and monitored the response. The measurements were then processed by a machine learning algorithm to enable a prediction of the battery's health and useful life.