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SpaceX’s Starship rocket just took a big leap towards orbit with latest test success
A full-scale Starship rocket has passed a critical test for the first time ever, strongly suggesting that the next-generation launch vehicle could be much closer to orbital readiness than most would imagine.
To be clear, a huge amount of work remains before Starship can be deemed anywhere close to its first orbital flight tests, not the least of which is the fabrication and assembly of the first massive Super Heavy booster(s). However, after Starship SN4’s latest successful May 9th test, it’s hard to see any apparent showstoppers that can’t be handled with a combination of fairly routine testing and iterative progress, as well as time and money. There is certainly room for improvement throughout the program but SpaceX has effectively demonstrated that the biggest practical concerns about its approach to Starship are moot.
Captured live on May 9th and 10th by local resident and photographer Mary (bocachicagal) with the help of NASASpaceflight.com, SpaceX worked for about two days to reconfigure its fourth full-scale Starship prototype after two successful Raptor engine static fires and prepare it for a different kind of test. That work mainly involved removing said Raptor and replacing it with a hydraulic ram stand used to simulate the thrust of 1-3 engines without actually needing to perform a static fire test, further allowing SpaceX to simulate much longer engine operations than its spartan test pad could survive. Around 9pm CDT on May 9th (02:00 UTC, May 10), Starship SN4’s latest trial began.
Known as a cryogenic pressure and load test, it differed from a prior “cryo proof test” completed on April 26th, in which Starship was fully loaded with liquid nitrogen (more than twice as cold as dry ice), pressurized to a bit less than 5 bar (~70 psi), and stressed with hydraulic rams. About a week later, after installing a Raptor engine on a full-scale Starship prototype for the first time ever, Starship SN4 fired up said engine on May 5th – another historic first for the next-generation launch vehicle. 30 hours later, SpaceX performed another wet dress rehearsal (WDR) with liquid methane and oxygen and fired up Starship’s Raptor engine again.
After about 48 hours of reconfiguration, SpaceX moved on to a much more serious cryogenic test. As noted by CEO Elon Musk, the 4.9 bar the rocket previously reached was accepted as enough to perform a Raptor static fire test and possibly enough for a low-stress, low-altitude flight test to ~150m (500 ft). For orbital flight, however, Starship needs to withstand a minimum of 6 bar (~90 psi), while 8.5 bar (125 psi) is preferable to give the rocket the 1.4x safety factor optimal for human spaceflight.
This time, SpaceX – having successfully gathered data from two static fire tests and several wet dress rehearsals – was ready to risk Starship SN4 and pressurized it all the way to 7.5 bar (~110 psi). While ~12% shy of minimum human spaceflight standards, Starship SN4 successfully reached and maintained 7.5 bar while the ship stressed with hydraulic rams to simulate the thrust of three Raptor engines, all of which it survived fully intact. What 7.5 bar does offer, however, is a 1.25x safety factor – on the higher end of aerospace industry standards for uncrewed orbital spaceflight (i.e. cargo/satellite launches).
Ready for orbit?
Technically, this means that – pending much additional testing and verification with different serial prototypes and (likely) higher pressures – Starship’s stainless steel structure is effectively qualified for uncrewed orbital launches. Of course, reality is much more complex. To actually perform and survive orbital flights, SpaceX will first need to build and similarly qualify the first Super Heavy boosters and ensure that those unprecedentedly large rockets can survive and sustain ~20-30 Raptor engines firing simultaneously.
Aside from Super Heavy, it’s unknown if SpaceX has begun testing Raptor engines at the durations they will need to burn to booster Starships into orbit (TBD; likely 5-10 minutes of continuous operation). Along those lines, SpaceX also needs to build, test, and qualify Raptor’s vacuum-optimized sibling to complement the sea level version’s smaller, less-efficient nozzle. Still, Musk has already revealed that RaptorVac could be a matter of weeks from its first static fire and rocket engine development – while incredibly challenging – is more of a known quantity for SpaceX.
Perhaps the most important unknown is whether SpaceX’s recent May 2020 WDRs and static fires have used autogenous pressurization, a more efficient method of pressurizing rockets by using hot gas generated by their own engines. It’s extremely likely that SpaceX has been autogenously pressurizing Starship SN4 for its recent tests, but if that weren’t the case, it would be a big source of schedule uncertainty without significant redesign work.
Ultimately, SpaceX appears to have proven that orbital-class rockets can be built cheaply out of commodified steel in extraordinarily spartan production facilities. Many, many challenges remain but the biggest uncertainty and hurdle facing SpaceX’s Starship program and ambitions is well on its way to being fully put to rest.
Turn-by-turn navigation is not new technology.
For over two decades, drivers have relied on Garmin, TomTom, and later smartphone apps like Google Maps and Waze to receive precise, reliable directions. These systems have guided millions safely through unfamiliar cities, highways, and backroads with remarkable effectiveness. They handle real-time traffic, construction detours, and complex intersections with minimal fuss.
Yet Tesla, the company that promised revolutionary Full Self-Driving (FSD), continues to struggle with this foundational capability. As FSD (Supervised) v14.3.4 has started rolling out to cars this week, navigation remains its glaring Achilles’ heel, undermining the entire autonomous vision.
Tesla Summon got insanely good in FSD v14.3.2 — Navigation? Not so much
Tesla’s FSD excels in many driving behaviors—smooth acceleration, confident lane changes in ideal conditions, and responsive handling of visible obstacles. However, when it comes to following a route accurately, the system falters repeatedly.
Owners report wrong turns, missed exits, inefficient routing through local roads instead of highways, phantom speed limit errors, and even directing vehicles to building rear entrances. Interventions for navigation issues often outnumber those for core driving maneuvers. Tesla has begun surveying owners specifically about these errors, acknowledging the problem after years of complaints.
Navigation is perhaps my biggest complaint when it comes to FSD, because sometimes, we do know better. Some of us have been living in our areas for our entire lives, but even those who have not have years or even decades of experience driving on local roads. We might know a little better about routing.
But the navigation mistakes are more than just FSD potentially taking a slightly different route that may or may not save you a few minutes. Sometimes, they’re genuinely mind-boggling.
This isn’t just annoying; it cascades into broader failures. A flawed route plan confuses the AI’s decision-making, leading to hesitant behavior, unnecessary disengagements, or dangerous maneuvers like attempting impossible U-turns or ignoring clear ramps. In a system meant to operate with minimal supervision, unreliable navigation erodes trust.
More often than not, false or plain incorrect navigation is what causes me to interrupt FSD operation. Unfortunately, I believe the latest FSD version is the worst example of it, and it leads me to believe that Tesla might be making some changes; they’ve just made them in the wrong direction.
It makes you wonder: Why is a company that has done so much with the progress of FSD and autonomy struggling so much with navigation, something that is not new and has been around a long time?
Multiple Data Sources
First, Tesla’s navigation relies on a fragile patchwork of multiple data sources—Google Maps, TomTom, OpenStreetMap, Valhalla, and its own fleet-derived data—stitched together rather than a single authoritative map. When these conflict on lane geometry, road status, or turn details, the system hesitates or chooses incorrectly.
Traditional GPS providers maintain centralized, regularly validated databases with professional curation and rapid updates. Tesla’s hybrid approach, while innovative in crowdsourcing, introduces inconsistencies that a purely vision-based or end-to-end AI approach may not easily reconcile in real time.
Persistent Learning
FSD seems to struggle with persistent learning from driver interventions.
Unlike consumer apps that quickly adapt to repeated corrections or user preferences (e.g., avoiding certain routes or remembering habitual detours), Tesla’s FSD often fails to internalize fixes on the same trip or across similar scenarios. Owners note making the same manual override multiple times without the routing engine updating its behavior meaningfully.
This stems from the neural architecture prioritizing real-time perception and control over long-term route memory and personalization, making navigation feel rigid and “opinionated” compared to the adaptive logic in Waze or Google Maps.
I noticed that when I asked Grok to try and get me home a certain way (a way that FSD routinely took in the past because it was the most efficient), it had to place a waypoint between my location at the time and my house. When I went to edit the waypoint out, as Grok had placed it for a way to get FSD to get off the highway at the right exit, it was stumped again, rerouted, and took a longer way home.
The next thing I’ve noticed, and this might be controversial, is that Nav has gotten even worse.
I think that might actually be a good thing; Tesla seems to be adjusting it. They just need to adjust it the opposite way.
The car is taking extremely strange routes to very… https://t.co/UHg3tVfNA2
— TESLARATI (@Teslarati) June 16, 2026
Reasoning, Scaling, and Intuition
Third, scaling navigation for unsupervised or robotaxi ambitions requires not just accuracy but adaptability and user-like reasoning. Current FSD often defaults to single routes that ignore driver preferences or real-world nuances like time-of-day traffic patterns. It fails to match the intuitive, context-aware planning that traditional systems have refined over the years.
Resolving navigation is critical for several reasons. Practically, it is the backbone of any autonomous journey: without trustworthy routing, the car cannot reliably reach destinations, rendering FSD useless for robotaxis or hands-free commutes. Safety depends on it—mismatched plans create hesitation in merges or intersections, increasing accident risk.
Economically, Tesla’s valuation and future hinge on FSD delivering unsupervised driving; persistent navigation flaws delay regulatory approval and erode consumer confidence. For owners who paid premiums for FSD, these issues represent unfulfilled promises. While it is unlikely Tesla will lose too many customers due to bad navigation, some will be frustrated with the constant need for human input.
Tesla has achieved miracles in electric vehicles and battery tech. Mastering turn-by-turn—technology Garmin nailed in the early 2000s—should not be this hard. By investing in tighter data integration, faster learning loops from interventions, and more intuitive routing algorithms, Tesla could close this gap.
Until then, FSD’s navigation struggles highlight a humbling truth: even the most ambitious innovator must sometimes master the basics before conquering the future.
A Tesla Cybertruck driver in the United Kingdom had their all-electric pickup seized by local police in the Greater Manchester area after the department cited “legitimate concerns.”
Last Thursday, police saw the pickup on the roads and decided to pull the driver over. Greater Manchester Police said:
“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a collision with the Cybertruck.”
🚨 A Tesla Cybertruck, which is illegal to drive in the UK due to safety concerns, has been seized by police in Greater Manchester
“Whilst this may seem trivial to some, legitimate concerns exist around the safety of other road users or pedestrians if they were involved in a… pic.twitter.com/cqhdPok3DM
— TESLARATI (@Teslarati) June 16, 2026
The Cybertruck in question was, according to the BBC, registered and insured abroad and was confiscated. The driver, who is a UK resident, was reported.
The Greater Manchester Police Department then added:
“The Tesla Cybertruck is not road-legal in the UK and does not hold a certificate of conformity.”
The Cybertruck cannot be legally driven in the UK because it has no UK Type Approval for operation in the country. This is due to some safety concerns, which are related to its angular shape and design. The stainless steel exoskeleton has sharp edges and projections that violate UK/EU rules on pedestrian protection.
Tesla has considered creating what it referred to as an “international version” that would be approved for operation in Europe. However, there has been no real movement on that front by the company, as it has been focused on the Robotaxi rollout primarily.
A new report claims that Apple is in the process of developing what would be the missing link for Tesla to get CarPlay.
Apple and Tesla have been reportedly working together for some time to give Tesla owners the opportunity to utilize CarPlay within their vehicles. While many owners are more than happy with Tesla’s in-house UI, which is seamless, effective, and smooth, some still want CarPlay, which does have its advantages.
A report from 9to5Mac now states that a new CarPlay technology that was highlighted during the Worldwide Developers Conference (WWDC) would potentially be the bridge between Tesla and Apple. With the addition of a feature known as “Route Sharing,” which gives a navigation app the ability to share routing data with the vehicle, Tesla would be able to launch CarPlay in its vehicles, the report states.
CarPlay has not been a priority for Tesla because it has done extremely well with its in-house UI, but some drivers are just used to it. Additionally, it could improve Tesla’s subpar Navigation or offer improved app capabilities, especially with iMessage.
Route Sharing is an intended addition to CarPlay’s iteration in iOS 26.4, which was released in March:
The addition of CarPlay would undoubtedly be welcome, but at the same time, it seems like Tesla realizes it is not of the utmost priority. There are so many things that Tesla is working on currently within its own vehicles, especially attempting to solve self-driving.
Back in February, Bloomberg had reported that Tesla was still working on bringing CarPlay to its vehicles, but it had not due to app compatibility issues and incredibly low adoption rates of iOS 26.
This bottleneck could buy Tesla the proper amount of time to develop CarPlay for its vehicles. It would be a welcome addition, and could be brought on with either the Summer or Fall 2026 Software Updates.
Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest
Tesla Cybertruck driver gets pickup seized for ‘legitimate concerns’ in UK
