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SpaceX preparing for third Starship ‘full stack’

Booster 4 and Ship 20 - March 13th, 2022. (NASASpaceflight - bocachicagal)

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SpaceX appears to be preparing Starship 20 and Super Heavy Booster 4 for their third ‘full stack’ demonstration after two seemingly successful tests in August 2021 and February 2022.

The first, completed in early August 2021, was mostly for show and saw SpaceX stack the unfinished prototypes with a giant crane – fighting the coastal winds throughout. After just a few hours stacked, Ship 20 was removed and returned to Starbase, where workers spent several more weeks (mostly) finishing the prototype. Booster 4 followed suit several weeks later and ultimately took another three months of work to reach some level of test readiness.

After Ship 20 and Booster 4 completed a series of tests in the last few months of 2021 and early 2022, the two were re-stacked in mid-February – once again for show. This time, the stacked Starship served as a backdrop for SpaceX CEO Elon Musk’s first official Starship presentation in more than two years. However, despite the fact that neither prototype was actually tested during the second stack, SpaceX did use the opportunity to partially debut Starbase’s ‘orbital launch integration tower’ and used that towers trio of giant arms to lift, stack, and stabilize Starship S20 on top of Super Heavy B4.

The first stack. (SpaceX)
Stack #2.

Ship 20 was ‘destacked’ with the tower’s arms just a few days after Musk’s event – an undeniably rapid and impressive achievement for the first real use of the ‘chopstick’ arms but still far from demonstrating that Ship 20, Booster 4, or the orbital launch site (OLS) are ready for orbital test flights. Since then, however, Starbase’s launch facilities have admittedly been almost as busy as they’ve ever been with Starship and Super Heavy cryoproof tests.

Ship 20 completed its first basic OLS cryogenic proof test or ‘cryoproof’ just two days after it was destacked. Additional Starship S20 cryoproofs followed on February 17th (the day after), February 22nd, and March 3rd. Super Heavy B4 completed its own cryoproofs on February 18th and March 1st, the latter of which may have actually been the fullest a Starship booster has ever been filled. All told, SpaceX completed no less than six major B4/S20 cryoproof tests in 15 days.

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https://twitter.com/NASASpaceflight/status/1494100158761648128

Crucially, all six cryoproofs were performed with Starbase’s nascent orbital tank farm, thoroughly testing its storage and distribution capabilities. Additionally, because SpaceX began liquid methane deliveries on February 13th, some of those tests – particularly with Ship 20 – may have even been proper wet dress rehearsals, meaning that SpaceX may have filled the rocket(s) with liquid methane (LCH4) and liquid oxygen (LOx) propellant to replicate preparations for a real launch.

At a minimum, Super Heavy Booster 4’s oxidizer tank was fully filled with liquid oxygen – and possibly pressurized with hot gaseous oxygen – during its March 1st cryoproof, while its fuel tank was filled about two-thirds of the way either with liquid nitrogen (LN2) or methane. Prior to its February and March tests, Booster 4 had already completed three cryoproofs – some also using LOx – in December 2021. Ship 20 had completed a cryoproof and four static fire tests.

A six-engine Ship 20 static fire. (SpaceX)

All told, short of finally performing a full Super Heavy wet dress rehearsal and static fire at the orbital launch site, it’s not all that clear what more SpaceX can derive from additional individual cryoproof testing of Ship 20 or Booster 4. Several things do still need to be demonstrated, however. First, the OLS launch tower has yet to use its arms to remotely install a Super Heavy on the orbital launch mount. More importantly, SpaceX has yet to use the launch tower and its swinging ship umbilical arm to cryoproof or fuel a Starship while stacked on top of a Super Heavy. Finally, SpaceX has also yet to simultaneously perform a cryoproof or wet dress rehearsal test of a stacked Starship and Super Heavy, which will be necessary for orbital test flights.

One or several of those to-be-completed tests may be why SpaceX appears to have begun preparing to install Ship 20 on top of Booster 4 for the third time. On March 14th, Starship S20 was moved towards the launch tower and on March 15th, the ship was slotted between its ‘chopstick’ arms. Based on stack #2, the ship could be lifted at any point – day or night – and installed on top of Super Heavy in a matter of hours.

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Eric Ralph is Teslarati's senior spaceflight reporter and has been covering the industry in some capacity for almost half a decade, largely spurred in 2016 by a trip to Mexico to watch Elon Musk reveal SpaceX's plans for Mars in person. Aside from spreading interest and excitement about spaceflight far and wide, his primary goal is to cover humanity's ongoing efforts to expand beyond Earth to the Moon, Mars, and elsewhere.

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Tesla urges New Jersey owners to oppose new bill that could block Robotaxi

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Credit: Grok

Tesla has launched a direct campaign targeting its customers in New Jersey, sending emails that warn of pending legislation that could effectively block true driverless technology in the state.

The email focuses on Senate Bill S.1677 and Assembly Bill A.3968, measures intended to create a three-year autonomous vehicle pilot program but laden with requirements that Tesla argues make unsupervised Robotaxis impossible.

According to the email, the bills impose “restrictions so severe that true driverless deployment would remain illegal.” Specific hurdles include mandates for human safety drivers during operations, multimillion-dollar insurance minimums, reportedly $5 million, and thresholds like 100,000 miles of demonstrated safe autonomous driving before any driverless approval.

Tesla contends these are arbitrary barriers that ignore real-world performance data and favor entrenched competitors over innovative technologies like its Full Self-Driving (FSD) system.

The push comes as Tesla has started expanding Robotaxi operations in states like Texas, where unsupervised vehicles are already providing rides in several cities. New Jersey, by contrast, risks falling behind. The company highlights in the email communication that more than 94 percent of serious crashes result from human error, meaning impairment, distraction, or fatigue. These are all problems that Robotaxis eliminate entirely.

In 2025, New Jersey recorded 582 traffic deaths, underscoring the human cost of delayed adoption.

Tesla’s outreach stresses the transformative potential of robotaxis. For families, they could offer safer school runs without drowsy or distracted drivers. For seniors and people with disabilities, robotaxis promise independence and reliable mobility.

In areas with limited public transit, they could deliver affordable, on-demand transportation, reducing congestion, emissions, and overall transportation costs. Economically, the company warns that restrictive rules could cost New Jersey jobs, innovation investment, and billions in potential growth as autonomous ride-hailing scales elsewhere.

Supporters of the legislation, including Sen. Andrew Zwicker, describe the pilot as a cautious framework with strong safety oversight, including incident reporting, expert task forces, and restrictions in sensitive zones like school areas. They view it as balancing innovation with public protection.

Tesla and pro-AV advocates counter that the bill lacks technology neutrality, creates insurmountable entry barriers for commercial deployment, and prioritizes process over outcomes — effectively functioning as a de facto ban on services like Robotaxi.

This latest clash echoes Tesla’s past battles in New Jersey over direct vehicle sales. The email directs owners to Tesla’s advocacy platform, where they can send customized messages to legislators calling for amendments: outcome-based safety standards, open competition, and clear pathways for fully driverless commercial operations.

As hearings approach, Tesla’s campaign frames the issue as a choice between protecting the status quo and embracing life-saving progress. With robotaxi technology already proving itself in permissive states, New Jersey owners are being asked to ensure their state doesn’t lock out the future of transportation.

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Tesla’s Navigation Nightmare: Why the easiest part of FSD might be the hardest

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Credit: TESLARATI

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.

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.

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Tesla Cybertruck driver gets pickup seized for ‘legitimate concerns’ in UK

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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.”

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.

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