The fastest electric vehicle charging stations currently get an empty battery to 80 percent full in about 30 minutes. But a new company is working on swapping out empty battery packs for fully charged ones. That would get an electric vehicle to 100 percent full in about 10 minutes. Ample, which officially launched this week at two sites in San Francisco and another Oakland, builds and operates battery-swapping stations that use a robot to pluck out dead battery packs from under the car and replace them with packs fully charged and ready to go. The Ample stations can be set up anywhere close to a power source so that the robot machine can get under the belly of the car and also charge a waiting supply of replacement batteries. The stations are completely autonomous and you don't even have to get out of the car while the batteries are switched.
Tesla has given the first look at its new tabless battery cell, dubbed 4680, and Roadrunner production line that, according to CEO Elon Musk, 'will make full-size cars in the same way to cars are made.' The tabless battery was first unveiled in September during the firm's Battery Day, but was only shown by Musk via a PowerPoint presentation. Now, the time has come for Musk to show the world what Tesla has been working on at its pilot battery factory in Fremont, Texas. The one-minute clip shows the white and blue battery moving through different assembly stages with the help of armed and wheeled robots. Tesla also used this opportunity to announce it is taking applications for manufacturing jobs at its planned battery facilities in Berlin and Texas.
SAN RAMON, California – Tesla is working on new battery technology that CEO Elon Musk says will enable the company within the next three years to make sleeker, more affordable cars that can travel dramatically longer distances on a single charge. But the battery breakthroughs that Musk unveiled Tuesday at a highly anticipated event didn't impress investors. They were hoping Tesla's technology would mark an even bigger leap forward and propel the company's soaring stock to even greater heights. Tesla's shares shed more than 6 percent in extended trading after Musk's presentation. That deepened a downturn that began during Tuesday's regular trading session as investors began to brace for a potential letdown.
This paper presents a novel algorithm, called $\epsilon^*$+, for online coverage path planning of unknown environments using energy-constrained autonomous vehicles. Due to limited battery size, the energy-constrained vehicles have limited duration of operation time. Therefore, while executing a coverage trajectory, the vehicle has to return to the charging station for a recharge before the battery runs out. In this regard, the $\epsilon^*$+ algorithm enables the vehicle to retreat back to the charging station based on the remaining energy which is monitored throughout the coverage process. This is followed by an advance trajectory that takes the vehicle to a near by unexplored waypoint to restart the coverage process, instead of taking it back to the previous left over point of the retreat trajectory; thus reducing the overall coverage time. The proposed $\epsilon^*$+ algorithm is an extension of the $\epsilon^*$ algorithm, which utilizes an Exploratory Turing Machine (ETM) as a supervisor to navigate the vehicle with back and forth trajectory for complete coverage. The performance of the $\epsilon^*$+ algorithm is validated on complex scenarios using Player/Stage which is a high-fidelity robotic simulator.
Amazon Scout, the e-commerce giant's fully-electric autonomous delivery robots, are heading south. Announced Tuesday in a blog post from Amazon Scout VP Sean Scott, Amazon says that it is set to start delivering to select customers in these markets as part of the company's continuing "field test" rollout. It has also been delivering packages in Snohomish County, Washington, and the Irvine-area of California. "We're thrilled to bring Amazon Scout to two new communities," Scott writes. "Adding Atlanta and Franklin to our existing operations gives Scout devices the opportunity to operate in varied neighborhoods with different climates than they operate in today. Amazon also has a significant presence in these areas through our corporate offices and logistics facilities. And, we know they are both great places to find world-class talent that can help us continue inventing for customers."
A battery pioneer has invented a new kind of battery that is 90 per cent cheaper to produce than standard lithium-ion batteries, and potentially much safer. Hideaki Horie – who has worked on battery technology since 1990 and led Nissan's development of the Leaf electric car – discovered a way to replace the batteries basic components in order to speed up and simplify the manufacturing process. "The problem with making lithium batteries now is that it's device manufacturing, like semiconductors," Mr Horie told The Japan Times. "Our goal is to make it more like steel production." Manufacturing the new batteries is significantly simplified by replacing the metal-lined electrodes and liquid electrolytes typically found within lithium-ion units with a resin construction.
Apple is rolling out a new feature called "battery health management" that will change how laptops charge themselves. The update will mean that laptops may not charge themselves all the way up all of the time, if the computer believes doing so will protect the life of the battery. It aims to avoid a problem that means fully charging a laptop's battery puts a strain on it, because of the chemicals inside. Leaving a computer charged up in this way can therefore reduce its capacity, leading the battery life to fall over time. Instead, if the computer believes that it is not likely to need 100 per cent battery in the future, it will only charge up some of the way.
The battery is a key component of autonomous robots. Its performance limits the robot's safety and reliability. Unlike liquid-fuel, a battery, as a chemical device, exhibits complicated features, including (i) capacity fade over successive recharges and (ii) increasing discharge rate as the state of charge (SOC) goes down for a given power demand. Existing formal verification studies of autonomous robots, when considering energy constraints, formalise the energy component in a generic manner such that the battery features are overlooked. In this paper, we model an unmanned aerial vehicle (UA V) inspection mission on a wind farm and via probabilistic model checking in PRISM show (i) how the battery features may affect the verification results significantly in practical cases; and (ii) how the battery features, together with dynamic environments and battery safety strategies, jointly affect the verification results. Potential solutions to explicitly integrate battery prognostics and health management (PHM) with formal verification of autonomous robots are also discussed to motivate future work. Keywords: Formal verification · Probabilistic model checking · PRISM · Autonomous systems · Unmanned aerial vehicle · Battery PHM. 1 Introduction Autonomous robots, such as unmanned aerial vehicles (UA V) (commonly termed drones 3), unmanned underwater vehicles (UUV), self-driving cars and legged-robots, obtain increasingly widespread applications in many domains .
Products/Services Visa agreed to acquire the token and electronic ticketing business of Rambus for $75 million in cash. The business involved is part of the Smart Card Software subsidiary of Rambus. It includes the former Bell ID mobile-payment businesses and the Ecebs smart-ticketing systems for transit providers. Meanwhile, Rambus expanded its CryptoManager Root of Trust product line. "Security is a mission-critical imperative for SoC designs serving virtually every application space," Neeraj Paliwal, vice president of products, cryptography at Rambus, said in a statement.
Rolnick, David, Donti, Priya L., Kaack, Lynn H., Kochanski, Kelly, Lacoste, Alexandre, Sankaran, Kris, Ross, Andrew Slavin, Milojevic-Dupont, Nikola, Jaques, Natasha, Waldman-Brown, Anna, Luccioni, Alexandra, Maharaj, Tegan, Sherwin, Evan D., Mukkavilli, S. Karthik, Kording, Konrad P., Gomes, Carla, Ng, Andrew Y., Hassabis, Demis, Platt, John C., Creutzig, Felix, Chayes, Jennifer, Bengio, Yoshua
Climate change is one of the greatest challenges facing humanity, and we, as machine learning experts, may wonder how we can help. Here we describe how machine learning can be a powerful tool in reducing greenhouse gas emissions and helping society adapt to a changing climate. From smart grids to disaster management, we identify high impact problems where existing gaps can be filled by machine learning, in collaboration with other fields. Our recommendations encompass exciting research questions as well as promising business opportunities. We call on the machine learning community to join the global effort against climate change.