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SpaceX rocket catch simulation raises more questions about concept
CEO Elon Musk has published the first official visualization of what SpaceX’s plans to catch Super Heavy boosters might look like in real life. However, the simulation he shared raises just as many questions as it answers.
Since at least late 2020, SpaceX CEO Elon Musk has been floating the idea of catching Starships and Super Heavy boosters out of the sky as an alternative to having the several-dozen-ton steel rockets use basic legs to land on the ground. This would be a major departure from SpaceX’s highly successful Falcon family, which land on a relatively complex set of deployable legs that can be retracted after most landings. The flexible, lightweight structures have mostly been reliable and easily reusable but Falcon boosters occasionally have rough landings, which can use up disposable shock absorbers or even damage the legs and make boosters hard to safely recover and slower to reuse.
As a smaller rocket, Falcon boosters have to be extremely lightweight to ensure healthy payload margins and likely weigh about 25-30 tons empty and 450 tons fully fueled – an excellent mass ratio for a reusable rocket. While it’s still good to continue that practice of rigorous mass optimization with Starship, the vehicle is an entirely different story. Once plans to stretch the Starship upper stage’s tanks and add three more Raptors are realized, it’s quite possible that Starship will be capable of launching more than 200 tons (~440,000 lb) of payload to low Earth orbit (LEO) with ship and booster recovery.
One might think that SpaceX, with the most capable rocket ever built potentially on its hands, would want to take advantage of that unprecedented performance to make the rocket itself – also likely to be one of the most complex launch vehicles ever – simpler and more reliable early on in the development process. Generally speaking, that would involve sacrificing some of its payload capability and adding systems that are heavier but simpler and more robust. Once Starship is regularly flying to orbit and gathering extensive flight experience and data, SpaceX might then be able refine the rocket, gradually reducing its mass and improving payload to orbit by optimizing or fully replacing suboptimal systems and designs.
Instead, SpaceX appears to be trying to substantially optimize Starship before it’s attempted a single orbital launch. The biggest example is Elon Musk’s plan to catch Super Heavy boosters – and maybe Starships, too – for the sole purpose of, in his own words, “[saving] landing leg mass [and enabling] immediate reflight of [a giant, unwieldy rocket].” Musk, SpaceX executives, or both appear to be attempting to refine a rocket that has never flown. Further, based on a simulation of a Super Heavy “catch” Musk shared on January 20th, all that oddly timed effort may end up producing a solution that’s actually worse than what it’s trying to replace.
Based on the simulated telemetry shown in the visualization, Super Heavy’s descent to the landing zone appears to be considerably gentler than the ‘suicide burn’ SpaceX routinely uses on Falcon. By decelerating as quickly as possible and making landing burns as short as possible, Falcon saves a considerable amount of propellant during recovery – extra propellant that, if otherwise required, would effectively increase Falcon’s dry mass and decrease its payload to orbit. In the Super Heavy “catch” Musk shared, the booster actually appears to be landing – just on an incredibly small patch of steel on the tower’s ‘Mechazilla’ arms instead of a concrete pad on the ground.
Aside from a tiny bit of lateral motion, the arms appear motionless during the ‘catch,’ making it more of a landing. Further, Super Heavy is shown decelerating rather slowly throughout the simulation and appears to hover for almost 10 seconds near the end. That slow, cautious descent and even slower touchdown may be necessary because of how incredibly accurate Super Heavy has to be to land on a pair of hardpoints with inches of lateral margin for error and maybe a few square feet of usable surface area. The challenge is a bit like if SpaceX, for some reason, made Falcon boosters land on two elevated ledges about as wide as car tires. Aside from demanding accurate rotational control, even the slightest lateral deviation would cause the booster to topple off the pillars and – in the case of Super Heavy – fall about a hundred feet onto concrete, where it would obviously explode.
What that slow descent and final hover mean is that the Super Heavy landing shown would likely cost significantly more delta V (propellant) than a Falcon-style suicide burn. Propellant has mass, so Super Heavy would likely need to burn at least 5-10 tons more to carefully land on arms that aren’t actively matching the booster’s position and velocity. Ironically, SpaceX could probably quite easily add rudimentary, fixed legs – removing most of the bad aspects of Falcon legs – to Super Heavy with a mass budget of 10 tons. But even if SpaceX were to make those legs as simple, dumb, and reliable as physically possible and they wound up weighing 20 tons total, the inherent physics of rocketry mean that adding 20 tons to Super Heavy’s likely 200-ton dry mass would only reduce the rocket’s payload to orbit by about 3-5 tons or 1-3%.
Further, per Musk’s argument that landing on the arms would enhance the speed of reuse, it’s difficult to see how landing Super Heavy or Starship in the exact same corridor – but on the ground instead of on the arms – would change anything. If Super Heavy is accurate enough to land on a few square meters of steel, it must inherently be accurate enough to land within the far larger breadth of those arms. The only process landing on the arms would clearly remove is reattaching the arms to a landed booster or ship, which it’s impossible to imagine would save more than a handful of minutes or maybe an hour of work. SpaceX’s Falcon booster turnaround record is currently 27 days, so it’s even harder to imagine why SpaceX would be worrying about cutting minutes or a few hours off of the turnaround and reuse of a rocket that has never even performed a full static fire test – let alone attempted an orbital-class launch, reentry, or landing.
Put simply, while Starbase’s launch tower arms will undoubtedly be useful for quickly lifting and stacking Super Heavy and Starship, it’s looking more and more likely that using those arms as a landing platform will, at best, be an inferior alternative to basic Falcon-style landings. More importantly, even if everything works perfectly, the arms actually cooperate with boosters to catch them, and it’s possible for Super Heavy to avoid hovering and use a more efficient suicide burn, the apparent best-case outcome of all that effort is marginally faster reuse and perhaps a 5% increase in payload to orbit. Only time will tell if such a radical change proves to be worth such marginal benefits.
Tesla AI lead Ashok Elluswamy said this week that 24-hour Robotaxi service is close. Replying on X to a rider who wanted Cybercab trips all night, he wrote that the capability would arrive “next month or so” once “the next tech to merge on the v15 plan” is ready.
The comment landed on September 4, one day after Tesla opened public Cybercab rides in Austin. It is the clearest near-term timeline yet for overnight unsupervised operation. Tesla’s paid Robotaxi network currently runs from 6 a.m. to 10 p.m. seven days a week across Austin, Dallas, Houston, Miami, Orlando, and Tampa.
next month or so. the next tech to merge on the v15 plan will enable it.
— Ashok Elluswamy (@aelluswamy) September 4, 2026
That 16-hour window is shorter than the 6 a.m. to 2 a.m. schedule the company used for much of the prior year.
Elluswamy did not name the specific feature or say whether the change would apply first to purpose-built Cybercabs, the existing Model Y fleet, or both. He also offered no city-by-city rollout list. The link to Full Self-Driving v15 is nevertheless significant.
Tesla has described v15 as a step-change architecture with seven parallel improvement tracks and roughly ten times more parameters than earlier builds. Early versions of that software already operate on the Robotaxi fleet and contain about 40 percent of the planned gains.
By July 2026, the unsupervised fleet had logged more than 380,000 miles across six cities in two states with what the company called an impeccable safety record and no notable incidents caused by the vehicles themselves. Tesla has repeatedly argued that camera-based end-to-end neural networks, rather than extra sensors, are the core of the solution.
Overnight service would test that claim in lower-light conditions and would also raise vehicle utilization, a key variable for Robotaxi unit economics. The company has already begun using public Superchargers at night and is building dedicated Robotaxi charging sites.
Riders have asked why software must change if the cars already drive in the dark. The practical answer appears to be reliability and scale: Tesla has held back mass expansion until more of the v15 stack is merged, citing the need for higher confidence before putting thousands of unoccupied vehicles on streets around the clock.
If the next module arrives on the timetable Elluswamy sketched, 24-hour service could begin in October 2026 in at least some markets.
That would mark a shift from a daytime-bounded pilot to a service that can run whenever demand exists, including the late-night hours that have so far remained out of reach.
Tesla is beginning to roll out Full Self-Driving Supervised v14.3.9 with a new active safety layer that can take control even when the driver is operating the car manually.
Tesla AI said the software can activate FSD on the driver’s behalf when an imminent collision is detected and Automatic Emergency Braking may not be enough. It may also engage if the system detects heavy distraction or an accidental FSD disengagement.
FSD Supervised v14.3.9 starting to roll out shortly
This release includes a new active safety feature set: FSD Supervised can now activate on your behalf when an imminent collision is detected and Automatic Emergency Braking (AEB) may not be enough.
It may also engage if we…
— Tesla AI (@Tesla_AI) September 4, 2026
The capability is essentially Automatic Collision Evasion. However, unlike conventional AEB, which mainly applies the brakes in a straight line, this feature can use steering, braking, and acceleration together if the car calculates that stopping alone will not prevent impact and a safer path exists. The system may change lanes or move toward a shoulder when conditions allow, then continue driving after the immediate threat is handled rather than simply coming to a stop.
The intervention is meant as a last-resort safety net, not a replacement for attentive driving.
Tesla Full Self-Driving v14.3.7 early review: FSD saved me from an accident
Tesla’s own description still frames FSD as supervised assistance. Secondary reports on internal release notes say the feature can fire while the car is being driven manually if cabin-camera monitoring suggests the driver is not sufficiently attentive, such as reaching toward the back seat, or if FSD appears to have been turned off unintentionally.
After the emergency maneuver, the car is expected to alert the driver and request a return to manual control.
The safety case is straightforward. Many collisions happen in the last second because a driver is looking away, fumbles a control, or faces an obstacle that braking cannot fully solve. A system that can both recognize that AEB is insufficient and execute a coordinated evasive path can reduce those remaining high-severity events.
Re-engaging after accidental disengagement also addresses a practical failure mode: a small steering nudge that drops FSD at the worst moment. The advantage is a background safety net that uses the same vision stack already running in v14, instead of leaving the car solely to emergency braking once the driver is no longer in command.
The feature still depends on FSD being enabled and, according to reports, an active FSD purchase or subscription. It does not make the vehicle unsupervised. Drivers remain responsible, and Tesla has not published how often the system is expected to intervene or how it will handle false positives.
If the rollout is conservative and the false-alarm rate stays low, the update is a meaningful step: FSD is no longer only a feature the driver turns on. In the rare moments when disaster is already forming, it can step in.
Tesla launched the all-electric, steering wheel-less, and pedal-less Cybercab last night at a quiet and small event in downtown Austin, Texas.
The launch, which marked the beginning of unsupervised ride-hailing for Tesla’s Robotaxi platform with Cybercab, has already caught the attention of the National Highway Traffic Safety Administration (NHTSA) who has more questions.
NHTSA opened an Audit Query (AQ) into the Cybercab’s Federal Motor Vehicle Safety Standards (FMVSS) certification that Tesla gave the vehicle. Manufacturers self-certify vehicles much of the time to avoid excessive regulatory delays.
Tesla Cybercab interior, note the lack of steering wheel and pedals. (Credit: @niccruzpatane/X< /a>)
However, the agency needs more information; it said in a summary:
“On September 3, 2026, Tesla began commercial deployment with a small number of its Cybercab vehicles in Austin, Texas. Tesla notified the Agency that it certified those Cybercab vehicles as compliant with all applicable Federal Motor Vehicle Safety Standards (FMVSS). Tesla also notified the Agency that it plans to gradually expand commercial deployment of the Cybercab to include additional vehicles and locations.”
It also went on to state that the Cybercab lacks traditional automotive controls, which is a groundbreaking move. The process is entirely new to the NHTSA, which gives the agency some leverage to put Tesla’s launch under a microscope:
“The vehicles lack permanently attached, conventional manual controls, such as a brake pedal, gas pedal, steering wheel, and mirrors. NHTSA is opening this AQ to examine the process and technical data on which Tesla relied when certifying the Cybercab and related issues. Among other things, NHTSA will consider the extent to which Tesla’s certification depended on determinations that certain FMVSS are inapplicable to the Cybercab.”
Tesla has added 45 Cybercab units to its fleet of Robotaxi-enabled cars in Austin, according to public documents the company submitted to the State of Texas over the past week. Enabling this level of self-driving is something Tesla has worked toward for many years, and now that it is finally here, it seems more than reasonable that regulatory agencies will have some questions.
Many outlets might try to frame this as a negative, but it is truly an agency looking to gain more information about groundbreaking tech that Tesla has been developing for years.
In an effort to keep riders, pedestrians, and property safe, any and all data accumulated from these first days, weeks, and months of rides will likely be shared with the NHTSA to enable broader rollout strategies across the United States and more in the future.
Tesla Robotaxi will be a 24/7 service: here’s when
Tesla Full Self-Driving will now overtake manual driving to avoid disaster
