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Tesla Smart Summon patent highlights progress in 3D labeling for full self-driving features

Tesla Smart Summon in action. (Credit: Rody Davis/YouTube)

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A recently published Tesla patent application details the machine learning methods behind Smart Summon, specifically highlighting the progress being made with 3D labeling in training data.

The application, titled “Autonomous and User Controlled Vehicle Summon to a Target,” utilizes machine learning methods explicitly detailed in two other recent Tesla patent publications in its functionality. This series of three inventions altogether describes an automated way of generating training data which is then used by a machine learning model to accomplish an expansive list of self-driving capabilities in Summon.

“Traditionally, much of the effort to curate a training data set is done manually by reviewing potential training data and properly labeling the features associated with the data,” Tesla’s first application in the series states. “The effort required to create a training set with accurate labels can be significant and is often tedious… Therefore, there exists a need to improve the process for generating training data with accurate labeled features.”

The application goes on to describe how labeled training data is made autonomously in their invention using sensors and the collection of what’s called a “time series,” i.e., a series of images captured over a period of time.

“Using data captured by sensors on a vehicle to capture the environment of the vehicle and vehicle operating parameters, a training data set is created,” it explains. “In some embodiments, a three-dimensional representation of a feature, such as a lane line, is created from the group of time series elements that corresponds to the ground truth… As one example, a series of images for a time period, such as 30 seconds, is used to determine the actual path of a vehicle lane line over the time period the vehicle travels…a single image of the group and the actual path taken can be used as training data to predict the path of the vehicle.”

Tesla CEO Elon Musk has previously mentioned that better labeling is one of the keys to speeding up the rollout of self-driving functionality and features like Reverse Summon. “We need to finish work on Autopilot core foundation code & 3D labeling, then functionality will happen quickly. Not long now,” Musk wrote on Twitter in March this year. With better labeling (more accurate training data) comes safer and more capable software due to improved predictions from the modeling.

Tesla Owners Silicon Valley Smart Summon Model 3s (Credit: @MinimalDuck)

When it comes to Tesla’s Smart Summon, prediction modeling is essential considering there isn’t a driver in the vehicle during its operation. The patent publication covering Summon embodies the first application’s time series functionality and a second application’s implementation of the time series’ training data in its methods, demonstrating one of the numerous potential uses for the machine learning invention. Hints about future developments using Smart Summon are also detailed in the application. Examples include:

  • Syncing the Smart Summon with a calendar so the vehicle “automatically navigates to arrive at the location at the ending time, such as the end of a dinner party, a wedding, a restaurant reservation, etc.”
  • Implementing a multi-part destination into the Summon instructions such as waypoints at an airport to pick up multiple passengers.
  • Monitoring the heartbeat of a Summon user to ensure they are maintaining a connection with the vehicle while operating the feature.
  • Customizing the vehicle’s arrival settings such as interior lighting, exterior lighting, hazard lights, welcome music, and climate control preferences.

One of the more unique bits about the Smart Summon patent application is the appearance of Elon Musk as an inventor. While the CEO is known to be intimately involved in nearly all aspects of vehicle design, software features, and business operations, his name is unexpectedly absent from most of the company’s inventions. However, this is apparently on purpose. “I generally try my best not to be on patents,” he revealed on Twitter in reply to a post about the Smart Summon application. Notably, inventorship is a legal definition based on the conception of an invention, i.e., not the person/people who suggested or directed its creation, but the person/people who devised the means to accomplish it.

Prior to the most recent patent publication, Musk contributed inventorship to the door and body styling of the Model X. He also contributed the same to both the design and function of Tesla’s vehicle charge inlets.

Accidental computer geek, fascinated by most history and the multiplanetary future on its way. Quite keen on the democratization of space. | It's pronounced day-sha, but I answer to almost any variation thereof.

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Tesla rolls out new Supercharging safety feature in the U.S.

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tesla's nacs charging connector
Credit: Tesla

Tesla has rolled out a new Supercharging safety feature in the United States, one that will answer concerns that some owners may have if they need to leave in a pinch.

It is also a suitable alternative for non-Tesla chargers, like third-party options that feature J1772 or CCS to NACS adapters.

The feature has been available in Europe for some time, but it is now rolling out to Model 3 and Model Y owners in the U.S.

With Software Update 2026.2.3, Tesla is launching the Unlatching Charge Cable function, which will now utilize the left rear door handle to release the charging cable from the port. The release notes state:

“Charging can now be stopped and the charge cable released by pulling and holding the rear left door handle for three seconds, provided the vehicle is unlocked, and a recognized key is nearby. This is especially useful when the charge cable doesn’t have an unlatch button. You can still release the cable using the vehicle touchscreen or the Tesla app.”

The feature was first spotted by Not a Tesla App.

This is an especially nice feature for those who commonly charge at third-party locations that utilize plugs that are not NACS, which is the Tesla standard.

For example, after plugging into a J1772 charger, you will still be required to unlock the port through the touchscreen, which is a minor inconvenience, but an inconvenience nonetheless.

Additionally, it could be viewed as a safety feature, especially if you’re in need of unlocking the charger from your car in a pinch. Simply holding open the handle on the rear driver’s door will now unhatch the port from the car, allowing you to pull it out and place it back in its housing.

This feature is currently only available on the Model 3 and Model Y, so Model S, Model X, and Cybertruck owners will have to wait for a different solution to this particular feature.

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LG Energy Solution pursuing battery deal for Tesla Optimus, other humanoid robots: report

Optimus is expected to be one of Tesla’s most ambitious projects, with Elon Musk estimating that the humanoid robot could be the company’s most important product.

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Credit: Tesla Optimus/X

A recent report has suggested that LG Energy Solution is in discussions to supply batteries for Tesla’s Optimus humanoid robot.

Optimus is expected to be one of Tesla’s most ambitious projects, with Elon Musk estimating that the humanoid robot could be the company’s most important product.

Humanoid robot battery deals

LG Energy Solution shares jumped more than 11% on the 28th after a report from the Korea Economic Daily claimed that the company is pursuing battery supply and joint development agreements with several humanoid robot makers. These reportedly include Tesla, which is developing Optimus, as well as multiple Chinese robotics companies.

China is already home to several leading battery manufacturers, such as CATL and BYD, making the robot makers’ reported interest in LG Energy Solution quite interesting. Market participants interpreted the reported outreach as a signal that performance requirements for humanoid robots may favor battery chemistries developed by companies like LG.

LF Energy Solution vs rivals

According to the report, energy density is believed to be the primary reason humanoid robot developers are evaluating LG Energy Solution’s batteries. Unlike electric vehicles, humanoid robots have significantly less space available for battery packs while requiring substantial power to operate dozens of joint motors and onboard artificial intelligence processors.

LG Energy Solution’s ternary lithium batteries offer higher energy density compared with rivals’ lithium iron phosphate (LFP) batteries, which are widely used by Chinese EV manufacturers. That advantage could prove critical for humanoid robots, where runtime, weight, and compact packaging are key design constraints.

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Tesla receives approval for FSD Supervised tests in Sweden

Tesla confirmed that it has been granted permission to test FSD Supervised vehicles across Sweden in a press release.

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Credit: Grok Imagine

Tesla has received regulatory approval to begin tests of its Full Self-Driving Supervised system on public roads in Sweden, a notable step in the company’s efforts to secure FSD approval for the wider European market. 

FSD Supervised testing in Sweden

Tesla confirmed that it has been granted permission to test FSD Supervised vehicles across Sweden following cooperation with national authorities and local municipalities. The approval covers the Swedish Transport Administration’s entire road network, as well as urban and highways in the Municipality of Nacka.

Tesla shared some insights into its recent FSD approvals in a press release. “The approval shows that cooperation between authorities, municipalities and businesses enables technological leaps and Nacka Municipality is the first to become part of the transport system of the future. The fact that the driving of the future is also being tested on Swedish roads is an important step in the development towards autonomy in real everyday traffic,” the company noted. 

With approval secured for FSD tests, Tesla can now evaluate the system’s performance in diverse environments, including dense urban areas and high-speed roadways across Sweden, as noted in a report from Allt Om Elbil. Tesla highlighted that the continued development of advanced driver assistance systems is expected to pave the way for improved traffic safety, increased accessibility, and lower emissions, particularly in populated city centers.

Tesla FSD Supervised Europe rollout

FSD Supervised is already available to drivers in several global markets, including Australia, Canada, China, Mexico, New Zealand, and the United States. The system is capable of handling city and highway driving tasks such as steering, acceleration, braking, and lane changes, though it still requires drivers to supervise the vehicle’s operations.

Tesla has stated that FSD Supervised has accumulated extensive driving data from its existing markets. In Europe, however, deployment remains subject to regulatory approval, with Tesla currently awaiting clearance from relevant authorities.

The company reiterated that it expects to start rolling out FSD Supervised to European customers in early 2026, pending approvals. It would then be unsurprising if the company secures approvals for FSD tests in other European territories in the coming months. 

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