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SpaceX returns Starship booster to factory after two major Raptor tests

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For the sixth time this year, SpaceX has returned the same Super Heavy booster prototype to its South Texas Starship factory after completing several tests.

Why is unclear. Super Heavy Booster 7 left the factory for the first time in March 2022 and has been stuck in a seemingly continuous state of testing, rework, and retesting ever since. While the pace of testing and progress was in many ways more aggressive from 2019 to mid-2021, it still can’t be said that SpaceX has been slacking off in 2022. Booster 7 alone completed more than 24 distinct tests (including six static fires) between early April and late November.

But in a shift from the first three or so years of steel Starship development, SpaceX CEO Elon Musk has ceased to be a consistent source of information on the purpose and results of many of those tests, even as NASA has begun to funnel hundreds of millions of taxpayer dollars into the Starship program. Save for occasional tidbits from SpaceX, Musk, and NASA; or deep unofficial analyses of public information, the day-to-day or week-to-week status of Starship has generally been relegated to speculation. Over the last few months, that information void has only grown larger.

Perhaps the biggest near-term update this year came from a senior NASA official on October 31st. In an advisory briefing, Mark Kirasich – Deputy Associate Administrator for Artemis Campaign Development – offered a surprising amount of detail about SpaceX’s near-term plans and even reported that Starship’s first orbital test flight was expected as early as December 2022, pending several crucial tests. But more than five weeks later, SpaceX appears to have only made a modest amount of progress towards those milestones and has yet to attempt the two most important tests.

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Nonetheless, some progress – however indeterminate without official information – has been made. As of Kirasich’s briefing, SpaceX was in the middle of a relatively minor series of cautious propellant loading tests with Booster 7 and Ship 24, which were stacked on October 20th. After three more partial full-stack tests in the first seven days of November, Ship 24 was removed. Aside from the visible steps SpaceX took after, little is known about the outcome of those propellant loading tests.

Ship 24’s fate is a different story, but Super Heavy B7 appeared to make it through full-stack testing in great shape. On November 14th, Booster 7 completed a record-breaking 14-engine static fire, doubling its previous record of seven engines and likely becoming one of the most powerful rockets in history. Musk simply stated that the “test went well”.

Poor weather undoubtedly contributed, but it would be another 15 days before Booster 7’s next test. On November 29th, after an aborted test on the 28th, SpaceX followed Booster 7’s record-breaking 14-engine static fire with a longer 13-second test of 11 Raptors. Before engine ignition, SpaceX loaded Booster 7 with around 2800 tons (~6.2M lb) of liquid oxygen (LOx) propellant in less than 90 minutes, making it a partial wet dress rehearsal (the methane tank was barely filled) as well. Musk called it “a little more progress towards Mars” and SpaceX shared a photo of the static fire on Twitter, but the results of the test – meant “to test autogenous pressurization” – were kept mostly opaque.

That uncertainty didn’t help when two of Booster 7’s 33 Raptor engines were removed immediately after the long-duration test. Then, Booster 7 was removed from Starbase’s lone ‘orbital launch mount’ on December 2nd and rolled back to the factory’s High Bay assembly facility on December 3rd. Historically, SpaceX has only returned Booster 7 to the factory to repair damage or install missing hardware. Without official information, it’s impossible to say why Booster 7 returned for the sixth time.

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The most optimistic explanation is that SpaceX brought the Super Heavy booster back to the factory to fully close out its engine section heat shield, which currently has 20 missing panels for each of its outer Raptor engines. But there’s a good reason that those panels were never reinstalled. Any replacements would need to be modified to ensure that the ad-hoc system installed to prevent the conditions that led to Booster 7’s first explosion from recurring can still be used for future static fire tests. Even then, it’s unclear why SpaceX would need to reinstall those panels now for Booster 7’s upcoming 33-engine static fire(s) and full-stack wet dress rehearsal(s) when they weren’t needed for 11 and 14-engine static fires and a dozen other fire-free tests.

Depending on why Booster 7 is back at the factory, there is a precedent for it returning to the launch site as early as next week. Alternatively, if major work or repairs are required, it could be six weeks before SpaceX returns the rocket to the launch pad. Given that the full wet dress rehearsals and one or several 33-engine static fires standing between Booster 7 and flight readiness will be riskier and more challenging than any other test the prototype has completed to date, there is no real chance that Starship will be ready for its first orbital launch this year.

In fact, without detailed information, especially regarding Ship 24’s mysterious state, it’s difficult to pinpoint a viable target for Starship’s orbital launch debut more specific than the first half of 2023. But with any luck, even if it requires a substantially longer wait, SpaceX’s recent decision to make Starbase move slower and break fewer things will hopefully pay off with a successful debut sometime next year.

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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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The Boring Company just doubled its tunneling power in Nashville

The Boring Company’s Prufrock MB2 is commissioned and ready to mine beneath Nashville’s streets.

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The Boring Company’s second tunnel boring machine, Prufrock MB2, is officially ready to dig in Nashville. The company confirmed the news on X, posting: “Prufrock-MB2 is ready to mine in Nashville! MB2 commissioning is complete, including the brief 11 rpm rotation shown here. Will MB2 catch up to MB1, who had quite the head start? And Prufrock-MB3 ships in August!”

MB2 arrives with meaningful improvements over its predecessor. Lessons learned from the launch and operation of MB1 have already been applied to MB2 to improve efficiency and prepare the machine for launch.

Traditional tunnel boring machines operate in a stop-and-go cycle, digging roughly five feet, halt, erect precast concrete segments to line the tunnel wall, then resume. That repeated interruption is one of the main reasons conventional tunneling is slow and expensive. Prufrock is designed to install the tunnel liner simultaneously with mining, eliminating the need to stop every five feet. The machine also skips the need for excavated launch pits. Prufrock arrives on a truck, tilts down, and launches into the ground within 24 hours. And when the tunnel is complete, it emerges from the ground and drives to its next launch site on a trailer, eliminating the need for expensive cranes or pit excavation. The machine is also fully electric and runs with zero people in the tunnel during normal operations, controlled remotely from a surface operations center.

It won’t be long before we hear of another major update on The Boring Company’s Music City Loop project – a planned underground transit network beneath Nashville that would move passengers in electric vehicles through a series of tunnels at highway speeds, and bypassing surface traffic entirely. Nashville was selected in part because of its strong rock conditions that suits the Prufrock machines well, and relatively less regulatory hurdles.

Progress has been steady on multiple fronts. All 37 permits and approvals required ahead of tunneling have been obtained, out of 45 total. Key wins include a fully executed TDOT tunnel permit authorizing 25 miles of tunnel, unanimous airport authority approval for a Nashville International Airport station, and the city’s first residential station agreement serving downtown tower residents.

With MB1 already tunneling, MB2 now commissioned, and MB3 shipping in August, Nashville is becoming something of a live proving ground for scaled tunnel boring. The broader ambition is not limited to one city. The Boring Company’s stated goal is to make underground transportation a practical alternative to surface roads across major metro areas. Nashville is one of many cities, including a successful Las Vegas tunnel system, where that idea is being put to the test at real speed.

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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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