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SpaceX rocket catch simulation raises more questions about concept

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4 years ago

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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.

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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.

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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 Full Self-Driving v14.1 first impressions: Robotaxi-like features arrive

Tesla Full Self-Driving v14.1 is here, and we got to experience it for ourselves.

Published

17 minutes ago

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October 8, 2025

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Tesla rolled out its Full Self-Driving v14.1 yesterday, its first public launch of its most robust and accurate FSD iteration yet. Luckily, I was able to get my hands on it through the Early Access Program.

The major changes in FSD v14.1 were revealed in the release notes, which outline several notable improvements in areas such as driving styles, parking, and overall navigation. Here’s what Tesla outlined fully in its release notes:

  • Added Arrival Options for you to select where FSD should park: in a Parking Lot, on the Street, in a Driveway, in a Parking Garage, or at the Curbside.
  • Added handling to pull over or yield for emergency vehicles (e.g. police cars, fire trucks, ambulances).
  • Added navigation and routing into the vision-based neural network for real-time handling of blocked roads and detours.
  • Added additional Speed Profile to further customize driving style preference.
  • Improved handling for static and dynamic gates.
  • Improved offsetting for road debris (e.g. tires, tree branches, boxes).
  • Improve handling of several scenarios including: unprotected turns, lane changes, vehicle cut-ins, and school busses.
  • Improved FSD’s ability to manage system faults and recover smoothly from degraded operation for enhanced reliability.
  • Added alerting for residue build-up on interior windshield that may impact front camera visibility. If affected, visit Service for cleaning!

I wanted to try it for myself. My big must-dos were my complaints with v13.2.9, which included parking when arriving at a destination, Navigation when leaving a destination, and definitely a general improvement in the car traveling at an acceptable rate of speed, even when using the “Hurry” driving style.

Here’s what I noticed with the new Full Self-Driving v14.1:

Speed Profiles are More Realistic

I am driving on “Hurry” about 95% of the time when utilizing Full Self-Driving. In past versions, most notably v13.2.9, my Tesla would slowly reach the speed limit, and it would tend to hang out at about 1-2 MPH either above or below it.

My first observation with v14.1 was the vehicle’s tendency to get right up to speed and, since I was still on Hurry, drive slightly above the speed limit. It never got out of line; it traveled at speeds I would typically drive at manually.

I think this is a big improvement on its own, because I felt that I was pressing the accelerator too frequently in past FSD versions. Oftentimes, it just wasn’t going fast enough to justify the “Hurry” label; it felt more conservative and more like a student driver than anything.

Check it out:

This was among my favorite improvements, and it was the first thing I noticed as the car navigated me to the Supercharger, where my next positive is.

Navigating into parking lots, self-parking at Supercharger

One of the changes noted in the Release Notes was the addition of Arrival Options, which allows the car to select the appropriate parking situation. Since I was going to charge, the car had already chosen “Charger” as the parking option.

Pulling into a gas station or convenience store, especially during work days, can be stressful, as they are usually congested and full of foot and vehicle traffic. In past FSD versions, I have noticed the car being slightly “jumpy” and even hesitant to proceed through the lot.

Driving through parking lots was a noticeable improvement. It seems as if the car is much more confident in making its way through, while still being aware and cautious enough to safely navigate to the Supercharger.

It then backed straight into a Supercharger stall, which was recently repaired and is once again active. I was actually upset it chose this specific stall because it had been inactive for a while. However, Tesla got this stall back up and running, the car chose it, and backed into the spot flawlessly:

This was super cool to experience, and I think it is a testament to how hard the Tesla AI team has worked. CEO Elon Musk recently stated that FSD would enable automatic parking at Superchargers, which was really awesome to experience firsthand.

I decided to leave the Supercharger and go to an auto parts store to pick up some interior cleaner and some microfiber towels. I love keeping my Tesla clean!

I also thought it would be a great opportunity to see how it would react to another parking lot, how it would navigate it, and let it choose a parking spot. It did it all flawlessly:

I had zero complaints about everything here. All of it was done really well.

Making a choice after being caught in the middle of an intersection

I arrived at a tight intersection in Dallastown, PA, and what my car did next has catalyzed quite a conversation on X.

It proceeded out into the middle of the intersection as the light was green. It had to yield to oncoming traffic, and while waiting, the light turned yellow, then red.

Most people, including myself, would have turned right and proceeded through the intersection since the car was already past the line. However, FSD chose to back up and wait for the next light cycle, which I felt was also a more than acceptable option:

There are some conflicting perspectives on what it chose to do here. Some said they would have proceeded and would want FSD to also proceed. I can agree with that perspective, but I also think it is not the worst thing in the world to back up. In Pennsylvania, I couldn’t find the exact law that says what is right or wrong. Instead, I did see that a left turn on red is only feasible when you’re going from a One-Way street to another One-Way.

I’m not totally sure what is “correct” here, but I think either option is fine. I have personally done both, and I’ve seen other drivers do both. I was more than fine with the car doing this, and I was honestly impressed that it did.

Navigated a busy grocery store lot, found suitable parking

This is not the busiest my local grocery store gets, but it was still congested enough for me to be impressed.

FSD decided to do one loop in the parking lot before it found a spot that it felt was good enough for me. I was perfectly fine with where it chose to park, and I thought it did a really great job. I was impressed with how stress-free I felt, as I have noted in the past that parking lots are definitely an area where Tesla needs to improve.

I was happy with its performance:

Strange right turn signal as if it saw an emergency vehicle

This was the first bug I noticed with FSD v14.1. While traveling on a local road, it put the right turn signal on and approached the curb as if it was pulling over for an emergency vehicle or as if it was going to park on the street.

It then realized its mistake and proceeded:

I’m not super sure what caused this, but I was a tad bit confused. There were no police cars, ambulances, or anyone with flashing lights to my rear. There was a dump truck on the other side of the road, and I almost felt like the way it navigated “around” that was probably what triggered it.

Navigation is still making strange decisions

I’ve written about navigation and my discontent with some of its decisions. It seems v14.1 didn’t resolve much of anything with navigation, and it did a couple of things wrong.

The first was that it tried to take the illogical and pointless path out of the Supercharger. I wrote about this a few days ago, as FSD tried to take my car the wrong way.

It did it again, but I overrode the decision, and it was all okay:

This is a minor issue, but it is still pretty frustrating. Hopefully, the navigation will learn after performing this adjustment after enough times.

The next navigation issue was more frustrating than the Supercharger one, especially considering it completely ignored the route. The navigation had the vehicle very clearly heading straight, but out of nowhere, the right turn signal went on. I overrode it, but the car still turned right, ignoring the navigation completely:

I ended up taking over here and driving until I could get to a stop sign.

Final Thoughts

I am really impressed with all of the changes Tesla made with FSD v14.1, and while there were a handful of bugs, things were tremendously better than v13.2.9.

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Nvidia CEO Jensen Huang regrets not investing more in Elon Musk’s xAI

The CEO stated that Nvidia is already an investor in xAI, but he wished he had given the artificial intelligence startup more money.

Published

3 hours ago

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October 8, 2025

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Credit: Elon Musk/X

Nvidia CEO Jensen Huang revealed that one of his investment regrets is not putting more money into Elon Musk’s artificial intelligence startup, xAI. 

Speaking in a CNBC interview, Huang said Nvidia is already an investor in xAI but wished he had given the artificial intelligence startup more money. This was due to Musk’s record of building transformative companies such as Tesla and SpaceX.

A new wave of transformative AI firms

Huang said he’s very excited about xAI’s latest financing round. He described Musk’s company as part of a powerful new generation of AI developers, alongside OpenAI and Anthropic. that are reshaping the computing landscape.

“I’m super excited about the financing opportunity they’re doing. The only regret I have about xAI, we’re an investor already, is that I didn’t give him more money. You know almost everything that Elon’s pat of, you really want to be part of as well,” the Nvidia CEO stated.

The CEO also clarified Nvidia’s investment in xAI, revealing that Elon Musk had offered the investment opportunity to the chipmaker. “He (Musk) gave us the opportunity to invest in xAI. I’m just delighted by that,” Huang stated.

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AI investment boom

Huang contrasted today’s AI-driven economy with the early days of the internet. “Back then, all the internet companies combined were maybe $30 or $40 billion in size,” he said. “If you look at the hyperscalers now, that’s about $2.5 trillion of business already operating today.”

He also stated that the ongoing shift from CPU-based computing to GPU-powered generative AI represents a “multi-trillion-dollar buildout” that Nvidia is looking to support. Huang added that every Nvidia engineer now works with AI coding assistants such as Cursor, which he called his “favorite enterprise AI service,” and it has led to a major productivity boost across the company.

Watch Nvidia CEO Jensen Huang’s CNBC interview in the video below.

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Investor's Corner

Stifel raises Tesla price target by 9.8% over FSD, Robotaxi advancements

Stifel also maintained a “Buy” rating for the electric vehicle maker.

Published

4 hours ago

on

October 8, 2025

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Credit: Tesla China

Investment firm Stifel has raised its price target for Tesla (NASDAQ:TSLA) shares to $483 from $440 over increased confidence in the company’s self-driving and Robotaxi programs. The new price target suggests an 11.5% upside from Tesla’s closing price on Tuesday.

Stifel also maintained a “Buy” rating despite acknowledging that Tesla’s timeline for fully unsupervised driving may be ambitious.

Building confidence

In a note to clients, Stifel stated that it believes “Tesla is making progress with modest advancements in its Robotaxi network and FSD,” as noted in a report from Investing.com. The firm expects unsupervised FSD to become available for personal use in the U.S. by the end of 2025, with a wider ride-hailing rollout potentially covering half of the U.S. population by year-end.

Stifel also noted that Tesla’s Robotaxi fleet could expand from “tiny to gigantic” within a short time frame, possibly making a material financial impact to the company by late 2026. The firm views Tesla’s vision-based approach to autonomy as central to this long-term growth, suggesting that continued advancements could unlock new revenue streams across both consumer and mobility sectors.

https://twitter.com/AIStockSavvy/status/1975893527344345556

Tesla’s FSD goals still ambitious

While Stifel’s tone remains optimistic, the firm’s analysts acknowledged that Tesla’s aggressive autonomy timeline may face execution challenges. The note described the 2025 unsupervised FSD target as “a stretch,” though still achievable in the medium term.

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“We believe Tesla is making progress with modest advancements in its Robotaxi network and FSD. The company has high expectations for its camera-based approach including; 1) Unsupervised FSD to be available for personal use in the United States by year-end 2025, which appears to be a stretch but seems more likely in the medium term; 2) that it will ‘probably have ride hailing in probably half of the populations of the U.S. by the end of the year’,” the firm noted.

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