The Tesla and LVMH chiefs were joined by Maye Musk and Alexandre and Antoine Arnault at the ritzy Cheval Blanc hotel in the French capital.
Category: transportation
Tesla CEO Elon Musk thinks the automaker’s market capitalization is directly tied to whether the automaker is able to solve autonomous driving.
Superfast, subatomic-sized particles called muons have been used to wirelessly navigate underground for the first time. By using muon-detecting ground stations synchronized with an underground muon-detecting receiver, researchers at the University of Tokyo were able to calculate the receiver’s position in the basement of a six-story building.
As GPS cannot penetrate rock or water, this new technology could be used in future search and rescue efforts, to monitor undersea volcanoes, and guide autonomous vehicles underground and underwater. The findings are published in the journal iScience.
GPS, the global positioning system, is a well-established navigation tool and offers an extensive list of positive applications, from safer air travel to real-time location mapping. However, it has some limitations. GPS signals are weaker at higher latitudes and can be jammed or spoofed (where a counterfeit signal replaces an authentic one). Signals can also be reflected off surfaces like walls, interfered with by trees, and can’t pass through buildings, rock or water.
Mercedes owners in the U.S. will soon add a new luxury to their already luxurious vehicles: ChatGPT. The automaker is adding OpenAI’s conversational AI agent to its MBUX infotainment system, though what it could possibly be needed for is hard to say.
U.S. owners of models that use MBUX will be able to opt into a beta program starting tomorrow, June 16, activating ChatGPT functionality. This will enable the highly versatile large language model to augment the car’s conversation skills. You can join up simply by telling your car “Hey Mercedes, I want to join the beta program.”
It’s not really clear what for, though. After all, a car is a pretty well constrained environment. People need to drive, navigate, and control their media and the car’s basic functions, and certainly a voice interface is sometimes the safest or best option for doing so without taking their eyes off the road.
COPENHAGEN, June 14 (Reuters) — Swedish electric self-driving truck company Einride expects to reduce CO2 emissions in Norway by 2,100 tonnes over the coming three years as it partners up with Scandinavia’s leading postal service, PostNord, the company said on Wednesday.
Norway has the world’s highest number of electric vehicles per head of population and aims for all heavy vehicles to be zero-emission by 2040, potentially cutting CO2 emissions by 4.4 million tonnes or nearly 9% of the country’s annual emissions.
“Given Norway’s pioneering work in electrifying passenger vehicles, it’s only logical that they should take a leading role in the electrification of heavy-duty freight as well,” Einride CEO Robert Falck said.
The fascinating collective behaviors of biological systems have inspired extensive studies on shape assembly of robot swarms6,7,8,9. One class of strategies widely studied in the literature are based on goal assignment in either centralized or distributed ways10,11,12. Once a swarm of robots are assigned unique goal locations in a desired shape, the consequent task is simply to plan collision-free trajectories for the robots to reach their goal locations10 or conduct distributed formation control based on locally sensed information6,13,14. It is notable that centralized goal assignment is inefficient to support large-scale swarms since the computational complexity increases rapidly as the number of robots increases15,16. Moreover, when robots fail to function normally, additional algorithms for fault-tolerant detection and goal re-assignment are required to handle such situations17. As a comparison, distributed goal assignment can support large-scale swarms by decomposing the centralized assignment into multiple local ones11,12. It also exhibits better robustness to robot faults. However, since distributed goal assignments are based on locally sensed information, conflicts among local assignments are inevitable and must be resolved by sophisticated algorithms such as local task swapping11,12.
Another class of strategies for shape assembly that have also attracted extensive research attention are free of goal assignment18,19,20,21. For instance, the method proposed in ref. 18 can assemble complex shapes using thousands of homogeneous robots. An interesting feature of this method is that it does not rely on external global positioning systems. Instead, it establishes a local positioning system based on a small number of pre-localized seed robots. As a consequence of the local positioning system, the proposed edge-following control method requires that only the robots on the edge of a swarm can move while those inside must stay stationary. The method in ref. 19 can generate swarm shapes spontaneously from a reaction-diffusion network similar to embryogenesis in nature. However, this method is not able to generate user-specified shapes precisely. The method in ref. 21 can aggregate robots on the frontier of shapes based on saliency detection. The user-defined shape is specified by a digital light projector. An interesting feature of this method is that it does not require centralized edge detectors. Instead, edge detection is realized in a distributed manner by fusing the beliefs of a robot with its neighbors. However, since the robots cannot self-localize themselves relative to the desired shape, they make use of random walks to search for the edges, which would lead to random trajectories. Another class of methods that do not require goal assignment is based on artificial potential fields22,23,24,25. One limitation of this class of methods is that robots may easily get trapped in local minima, making it difficult to assemble nonconvex complex shapes.
Here, we propose a strategy for shape assembly of robot swarms based on the idea of mean-shift exploration: when a robot is surrounded by neighboring robots and unoccupied locations, it would actively give up its current location by exploring the highest density of nearby unoccupied locations in the desired shape. This idea does not rely on goal assignment. It is realized by adapting the mean-shift algorithm26,27,28, which is an optimization technique widely used in machine learning for locating the maxima of a density function. Moreover, a distributed negotiation mechanism is designed to allow robots to negotiate the final desired shape with their neighbors in a distributed manner. This negotiation mechanism enables the swarm to maneuver while maintaining a desired shape based on a small number of informed robots. The proposed strategy empowers robot swarms to assemble nonconvex complex shapes with strong adaptability and high efficiency, as verified by numerical simulation results and real-world experiments with swarms of 50 ground robots. The strategy can be adapted to generate interesting behaviors including shape regeneration, cooperative cargo transportation, and complex environment exploration.
Researchers claim the new electronic chip can mimic human vision and memory, which could help make self-driving cars smarter.
Researchers at the Royal Melbourne Institute of Technology (RMIT) have successfully developed a tiny electronic device that, they claim, can mimic human vision and memory. This could be a promising step to one-day developing sophisticated ways to make rapid decision-making in self-driving cars.
A team of engineers from RMIT University in Australia, along with researchers from Deakin University and the University of Melbourne, developed the device using a sensing element called doped indium oxide, which is thousands of times thinner than a strand of human hair and… More.
Engineers at MIT say they have developed a new motor that could be used to electrify large aircraft, significantly reducing their carbon footprint with the help of innovative new electric propulsion technology.
The 1-megawatt motor has already undergone design and testing of its primary components, which the MIT team says helps demonstrate that its power generation is comparable to current small aircraft engines.
Every year, pollution from carbon dioxide in excess of 850 million tons is produced by the aviation industry. If left unmitigated, those levels could increase by as much as three times by mid-century, concerns that have prompted caps on the carbon dioxide emissions of international flights that have been instituted in recent years.
Sphere Studios has developed a brand new type of cinema camera called The Big Sky. It features a single 316-megapixel HDR image sensor that the company says is a 40x resolution increase over existing 4K cameras and PetaPixel was given an exclusive look at the incredible technology.
The Big Sky cameras are not up for sale (yet) but they are meeting with film companies and filmmakers to find ways to bring the technology to the home-entertainment world. A discussion we had on-site revolved around gimbals mounted on helicopters, airplanes, and automobiles and how those systems, even “the best” still experience some jitter/vibration which is often stabilized which causes the footage to be cropped in.
The technology built for Big Sky helps eliminate a massive percentage of this vibration, and even without it, the sheer amount of resolution the camera offers can provide a ton of space for post-production stabilization. This alone could be a game changer for Hollywood when capturing aerial and “chase scene” footage from vehicles allowing for even more detail than ever before.
Researchers led by the University of California San Diego have developed a new model that trains four-legged robots to see more clearly in 3D. The advance enabled a robot to autonomously cross challenging terrain with ease—including stairs, rocky ground and gap-filled paths—while clearing obstacles in its way.
The researchers will present their work at the 2023 Conference on Computer Vision and Pattern Recognition (CVPR), which will take place from June 18 to 22 in Vancouver, Canada.
“By providing the robot with a better understanding of its surroundings in 3D, it can be deployed in more complex environments in the real world,” said study senior author Xiaolong Wang, a professor of electrical and computer engineering at the UC San Diego Jacobs School of Engineering.