As SpaceX Explodes Again, Honda Successfully Launches Reusable Rocket

Honda's reusable rocket blasts off in northern Japan.
The latest SpaceX rocket explosion is the fourth failure in a row for the company's embattled CEO and Tesla boss Elon Musk as he tries to rebuild his brand after controversial political aspirations.
Meanwhile, Honda—not meaning to shine a light of SpaceX problems—has just successfully conducted a launch and landing test of its experimental reusable rocket in northern Japan.
Honda's rocket climbed to 890 feet before landing just 15 inches away from where it took off.
Honda's rocket flew for 57 seconds and then landed
Honda is well-known in industry circles as one of the few carmakers who produces a multitude of non-car products including motorcycles, ATVs, power equipment such as generators, lawnmowers, outboard motors and snowploughs, the HondaJet and robots such as ASIMO. And now it's entered rocket R&D in earnest.
At Honda's test facility in Taiki Town located in Hokkaido, Japan's northern-most island, the company launched a reusable rocket that flew for almost a minute to an altitude of 890 feet and then landed with pinpoint accuracy just 15 inches from where it took off, according to Honda.
The rocket weighs 2800 lbs which equates to a small car.
Developed in-house by Honda R&D Company, the rocket—which weighs 2800 lbs or around the same weight as a small car—shot up vertically, blasting off using its four legs from the company's test site in the northern island of Hokkaido.
Honda says its Hokkaido facility 'has been developing itself as a 'space town' through the joint efforts of public and private sectors,' including the Japan Aerospace Exploration Agency (JAXA). The 21-foot high rocket, ascended for 57 seconds before landing around 15 inches from the target touchdown point using its four retractable legs that also aided in its take-off.
Honda first revealed its goal to go into space in late 2021. But while the carmaker has been tight-lipped about its R&D progress, it is using existing technology from other areas, such as automated driving systems, to assist in the development of its first reusable rocket.
The company says that the reason for developing its own launch system is the need for more satellites that will potentially benefit its other businesses.
According to Honda, its rocket research is still in its infancy, and no decisions have yet been made on potential commercialization of these rocket technologies. The company has the ambitious goal to enable a suborbital launch by 2029 but success here will require significant testing and perhaps a few failures.
A suborbital flight – upwards of 62 miles above sea level – would be a significant achievement for Honda, even though that is not far enough to put a satellite into orbit. It will be interesting to see if Honda goes all the way, and ends up competing with other private companies like SpaceX and Blue Origin that are capable of conducting orbital flights.

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Forbes

35 minutes ago

• Forbes

Safety Drivers, Remote Diving And Assist - The Long Tail Of Robotaxis

Remote driving room at Vay, where operators have video game consoles and multiple screens to control ... More cars on Las Vegas streets. With Tesla now planning to launch its pilot robotaxi service in Austin TX this week using safety drivers (Tesla employees in the passenger seat able to supervise and intervene) it's a good time to review the history of the safety driver and all the other technologies being used to help self-driving cars deal with the 'long tail' of problems they must solve to work on our roads. Making a car that can handle every possible road situation with perfect safety is a science fictional goal--nobody is close to knowing how to do it. As such, all robocars call on humans in one way or another, from tasks as simple as cleaning and recharging them to intervening when they make an unsafe move. I'll look at all approaches. Removing the safety driver is the 'big hard step' that changes a vehicle from a testing prototype to a real robotaxi. There are many other steps, but they are baby steps compared to the first time the vehicle goes out without a human overseeing it and able to take control. Safety Driver The very first robocars, which were pretty primitive and failed often, were set up so a human driver could sit in the driver's seat and grab the wheel or press the pedals at any time. That immediately disengaged the self-drive system and the car became manually driven. Many cars also had the 'big red button,' an emergency stop button to be used if grabbing the controls failed. It usually did a hard disconnect of all systems, but in practice most are never used. Outside of closed courses like the DARPA Grand Challenge, all robocar testing from day one has worked this way. All teams hope for the day they can remove that safety driver, as that is the whole goal. It generally works well. With properly behaving safety drivers, test robocars have very good safety records. Except for one giant black mark, when Uber ATG did not manage safety drivers well, and hired one who watched a TV show instead of doing her job, allowing the vehicle, when it failed (as prototypes are expected to do) to strike and kill a pedestrian. In the early years, cars typically had two staff in them, one behind the wheel, and the other, sometimes called the software operator, who monitored the driving soft ware to make sure it was doing the right things. Safety drivers can take the wheel at any time, and are told to do it if they feel anything odd is going on, or sometimes if a risky situation is likely. Especially in early years, if there were children on the street, you always took over. In addition, if the software detected any problems, it would alert the safety driver to take over. Teams (and governments) track interventions. The best teams take every significant intervention and create a simulation scenario to duplicate it, then test what would have happened if the human had not intervened. If the car would have done something bad, like hit something, that becomes a priority problem to fix. Indeed, interventions where it turns out the car would have done fine are often not even counted. Tesla took things to a new level when it released Autopilot and FSD. These had ordinary untrained customers act as supervisor for the vehicle. Google/Waymo had only used trained employees who took a driving safety course. When Tesla did this, there was great skepticism that relying on ordinary customers would be unsafe, but in reality, it worked out. Probably not as safe as ordinary driving, but fairly similar. (Tesla misleadingly claims it is much safer, but this is false.) Safety Driver not in Driver's Seat The normal place is behind the wheel, but some vehicles put a safety operator in another location, such as the passenger's seat. In vehicles designed with no controls (like some shuttles) the employee may have access to just an emergency stop button that commands the vehicle to stop and pull over, or slightly more involved controls. This may also include a video game controller, wheel or gamepad that can be plugged in for manual driving. This is probably not as safe as a person behind the wheel. In the passenger's seat, there is a ong history of human driving instructors training teen drivers by having their own brake pedal and the ability to grab the wheel. I remember my own driving instructor doing that. It works, though it's not clear if it has any purpose other than saying, 'nobody at the wheel.' It's more for PR than safety in vehicles that still have a wheel. Even so, some companies have done it. Russian robotaxi company Yandex used it in Austin and other cities. (Yandex is now non-Russian and called AVRide.) Cruise did their first 'driverless' test with an employee in the passenger seat. Most shuttle companies keep a worker in the shuttle who can hit the emergency stop, and pull out a game controller to drive. Remote Driving It may surprise some to learn there are remotely driven cars on the road today. German company Vay uses this to deliver cars to customers in Las Vegas. Several other companies have built different tools for remote driving. I worked (with compensation) with one such company, to produce a video about some of these approaches. Remote driving is done over public data networks, which of course face interruptions and packet loss and sometimes long latency. As such, it is typically done with a system capable of doing safe basic operations without remote input so that it will, at worst case, just come to a stop if comms get too bad. They are also usually designed to use multiple communications channels to survive problems with any one of them. Remote driving still requires paying a human, so you lose a lot of the cost advantage of a robocar over say, an Uber. However, you don't have to pay a human while the vehicle is sitting waiting. (Uber doesn't pay its drivers for that either, but it effectively builds into the fares for actual driving enough to make drivers tolerate the wait. They can also do other work or read or watch videos between rides.) As such, it can be cheaper to operate a remote driven fleet than a human driven one, and you can do WhistleCar service (car delivery) like Vay. Some companies, like Waymo, make use of low speed remote driving when they are in a situation where they want to move a stuck car or solve a problem the software can't. At these low speeds, you can't do much damage and you can stop on a dime if the connection has an issue. Some delivery robots, such as the early Kiwibot and Coco, were entirely remote driven, because at the speed of sidewalk delivery robots, that's fairy doable without safety concerns. (Indeed, many of these robots are so light that they don't hurt people even if they did hit them.) Tesla has advertised for programmers for some time to work on their remote driving and control systems for both robotaxis and the Optimus robot. Remote Supervision with Driving Remote supervision is effectively taking the safety driver and making them remote. The car mostly drives itself, but the remote supervisor is always watching (usually with an array of screens or possibly a VR headset) and 'grabs the wheel' virtually if they see the need to take over. You need to not need 'instant' takeovers that depend on sub-second reaction times (humans need about 0.7 seconds even when in the car) but is good for most problems which are apparent further in advance when you have the power of a human mind. This approach is not used by any team, at least publicly, though it has been speculated that Tesla is considering it. Remote Monitoring with Stop Most companies have the ability to connect to a car and watch what it's doing, even in full autonomous mode. Companies decline to comment on this, but all of them probably did this when they first dared to send the cars out with no safety driver. It seems like it would be foolish not to. Full time 1:1 remote monitoring doesn't scale very well, but it makes perfect sense in a pilot. In addition, these remote monitors probably have some ability to send a 'kill' command to the vehicle, to ask it to immediately stop and pull over, known as a 'minimum risk condition.' The difference between this and remote supervision is that these remote monitors can't do live steering, just hard stopping. Once stopped, however, they can usually switch into remote assist mode. Remote Assist All companies tend to have a remote assist operations room. There, operators are present who can help vehicles solve problems when they get confused. They usually cannot drive the vehicles directly, only give them strategic advice, like 'Turn around and take this new route' or 'Make the 2nd left' or 'Follow this set of waypoints to get around that obstacle' and most often 'Continue with your current plan, it's OK.' For remote assist to scale, you need to have many more vehicles on the road than remote assist operators, so that each vehicle on average needs active assist just a small fraction of the time. At Starship technologies, a delivery robot company, we set a goal of having 99% autonomy, meaning 100 robots for each operator. This makes the human labor cost effective. It's easier to do for delivery robots which can just stop and wait at any time. A leak from Cruise revealed robots were asking for help about every 5 minutes, which Cruise CEO Kyle Vogt felt was according to plan during their pilot stage. Over time the numbers would get better, but are never expected to get to zero. In most cases, according to Cruise, all the remote operator does is say, 'yes, continue with your plan A.' (In a typical remote assist, the vehicle sees a situation it is not fully sure of and offers multiple plans to the human remote operator, who picks one, or just allows plan A, or rarely crafts a new plan.) Sometimes remote operators will make human-like mistakes, which has been responsible for some strange incidents at Waymo, including one crash when the remote operator approved the vehicle going when it should not have. Some companies do have remote operators watching multiple cars at a time, which humans can do. While this may not scale long term, it's reasonably affordable today and wise during the pilot and growth stages of a robotaxi fleet. Waymo recently added the ability of remote operators to do low-speed remote drive to do things like move cars off the road, or out of trouble situations like blocked streets and emergency vehicles. Rescue Driver When all else fails, most teams can send humans in a car to rescue a vehicle by manually driving it, or in the worst case, towing it. For cars without controls, these teams will have a plug-in video game style controller. There are reports that some cars also have such a controller locked in a compartment that law enforcement can open so they can move cars without controls.

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Tesla's robotaxi plans to 'launch' for a limited number of users in Austin. Here's what we know.

Tesla's robotaxi service launch in Austin is expected Sunday, and some are already being spotted on the road. The anticipated launch comes years after several missed deadlines and an increasingly competitive — but shrinking — field. General Motors's Cruise recently bowed out of the race, but Alphabet's Waymo has continuously ramped up its service and is now providing 250,000 rides a week in the San Francisco Bay Area, Los Angeles, Phoenix, and Austin, according to the company. There's also Amazon's Zoox, which makes its own purpose-built robotaxi, and other software-focused companies that hope to provide autonomous driving features to original equipment manufacturer vehicles. However, Elon Musk swears by Tesla's approach to autonomy. On June 10, Musk reshared a video of a driverless Tesla with " Robotaxi" written on the side in Cybertruck font, making a left turn in Austin. He called its design "beautifully simple." "These are unmodified Tesla cars coming straight from the factory, meaning that every Tesla coming out of our factories is capable of unsupervised self-driving," Musk said in another tweet. During the company's Q1 earnings call in April, Musk described Tesla's self-driving capabilities as a "generalized solution using artificial intelligence." The CEO has touted this approach before, which refers to Tesla's reliance on cameras, as opposed to a pricey hardware stack made up of sensors and cameras, and an AI that will use the visual input to drive the vehicle. This could allow for Tesla to scale autonomy quicker and at lower costs since, in theory, any Tesla model could be deployed as a robotaxi. "I predict there will be millions of Teslas operating autonomously — fully autonomously — in the second half of next year," Musk said during the call. Musk recently provided more details about the coming robotaxi launch. Here's what we now know about Tesla's robotaxi service — and some lingering questions. What will Tesla's planned robotaxi rollout look like? Morgan Stanley analyst Adam Jonas, who recently visited Tesla's Palo Alto office, said that the robotaxi launch will take place on public roads and will be "invite only." Jonas also wrote that there will be "plenty of tele-ops to ensure safety levels." Teleoperators refer to remote workers who can take some control of the vehicle if the autonomous driver gets stuck. This strategy differs from Waymo and Zoox, which also have remote human workers to provide suggestions or information about a potential path forward if a driver gets stuck. BI previously reported that there had been discussion around using remote operators as safety drivers for the debut. How many robotaxis will be at the launch? It'll start small. Musk said in a May 20 interview with CNBC that Tesla will launch with around 10 robotaxis in the first week. The automaker will "then increase it to 20, 30, 40," Musk said. "It will probably be at 1,000 within a few months," Musk said. Tesla was careful to call the robotaxi service we'll see in June a "pilot" rollout in the automaker's first quarter earnings call, which hints at the limited scale of the initial launch. Musk has said he plans to expand the robotaxis to other cities, like San Francisco, following the Austin rollout, although he hasn't given an exact timeline on the expansion. "We just want to put our toe in the water, make sure everything is OK, then put a few more toes in the water, then put a foot in the water," Musk said during Tesla's fourth quarter earnings call in January. "With safety of the general public and those in the car as our top priority." By the end of 2026, Musk said there could be over 1 million self-driving Teslas in the country. "Once we make it work in a few cities, we can basically make it work in all cities in that legal jurisdiction," he said during a first-quarter earnings call. Which Tesla cars will be used for the robotaxi launch? The first set of Tesla robotaxis is expected to be Model Ys through a software update, according to Musk. The car spotted in Austin appears to be a refreshed Model Y with a robotaxi logo printed on its side. "With the software update, it will become autonomous," Musk said in the company's first quarter earnings call. "To be clear, the Model Ys that we're talking about being autonomous in Austin in June are the Model Ys we make currently. There's no change to it." It's unclear if the first batch of robotaxis will be managed directly by Tesla or if it will consist of privately owned Teslas through which owners will opt in to the service. The CEO also clarified that the Cybercab is a separate product. In October 2024, Tesla unveiled a purpose-built, two-door robotaxi with no steering wheel. "We've got a product called the Cybercab," he said during the first-quarter earnings call. "And then if any Tesla — which could be a (model) S, 3, X, or Y that is autonomous — is a robotic taxi or robotaxi. It's very confusing." What will the business model look like? Musk has compared the robotaxi business model to "some combination of Airbnb and Uber." Musk said during the CNBC interview that Tesla has "millions of cars that will be able to operate autonomously," and Tesla owners will have the opportunity to "earn money by adding their car to the fleet for autonomous use." "It's a combination of a Tesla-owned fleet and also enabling Tesla owners to be able to add or subtract their car to the fleet," Musk said. Musk added in the interview that Tesla owners could make more in allowing the car to be added to the self-driving fleet than the lease would cost. The Tesla CEO has previously said owners could earn about $30,000 a year from the service. "Just like Airbnb, you can rent out your spare bedroom or your house if you're not using it, and make money on it," Musk said. "And that's what we expect Tesla customers to be able to do." Tesla has yet to unveil the commercial version of its FSD Unsupervised software. The software will be used in the robotaxi fleet and doesn't need a driver behind the wheel like its personal vehicles. How can we order a Tesla robotaxi in June? Tesla teased its ride-hailing mobile app last year. A video of the app reveals a user requesting the service by pressing a black-and-white circle with the word "summon." Within a few seconds, the app shows a map of a car three minutes from the pickup location. The app also allows users to adjust the climate settings before it arrives. As of Sunday morning, several invited participants said they were still waiting for the app's release. So, when will we get the Cybercab? Tesla's Cybercab was unveiled at the "We, Robot" event last October. It's also a robotaxi, but it's a bit further out than the service launch date. Volume production of Cybercab is still on schedule for 2026, Lars Moravy, Tesla's vice president of vehicle engineering, said during the company's first quarter earnings call. Moravy said that the company is currently at the "B-sample validation" of the vehicle, which means Tesla is building the prototype of the car but using material that will be close to the final product. "Big builds" or the next stage of vehicle-building before volume production is coming at the end of the second quarter, Moravy said. Tesla anticipates that it will be able to pump out Cybercabs quickly at scale by using what the company calls its "unboxed" method of manufacturing. Traditional car manufacturers build cars on an assembly line. Tesla is betting on a new method where different parts of the car are simultaneously assembled and then later combined.

Yahoo

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GUANGZHOU , June 22, 2025 /PRNewswire/ -- In the fiercely competitive FMCG market, only efficient innovation can create a true competitive edge. As consumer preferences change rapidly and the market environment remains uncertain, how can companies precisely identify needs, execute efficiently, and continuously optimize their strategies? The Cyberway Product Innovation Platform empowers FMCG enterprises to achieve sustainable growth by providing powerful capabilities in pre-planning insight, in-process control, and post-launch analytics—ultimately enabling the development of exceptional product strength. Before: AI-Powered Foresight for Accurate Market Opportunity Detection AI Opportunity Discovery: Real-time industry data, user behavior, and competitor insights are captured to automatically identify blue ocean markets and unmet needs—fueling inspiration for new product planning. Accelerate Opportunity Capture: Shorten market research cycles and improve speed and accuracy of opportunity identification. AI-Driven Product Definition: Using opportunity and competitor analysis, combined with internal product knowledge bases, the system intelligently generates product concepts, optimizes configurations, and refines packaging and formulas. Agile Response: Ensure product design closely aligns with market needs and competition, allowing rapid focus on core value and improving product-market fit. End-to-End User Demand Management: A comprehensive demand management framework tracks records, statuses, and feedback, aggregating omnichannel voice of customer with AI to identify high-value & Accurate: By realizing and verifying demand in closed-loop cycles, continuously refine product performance, minimize resource waste, and pave the way for the next breakout product. 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Key Feature: Enables synergistic cooperation across departments for performance greater than the sum of its parts. AI Marketing: Tracks competitor strategies and social trends in real time, dynamically generating targeted content and pricing strategies using internal knowledge. Efficient & Agile: Accelerates creative production and drives an integrated "strategy-content-pricing" engine for rapid market response. Online Knowledge Repository: A dedicated enterprise R&D knowledge base aggregating key data such as risk warnings, solutions, and technical documentation. Significant Boost: Empowers faster troubleshooting and prevents redundant errors in R&D. Comprehensive Quality Control System: Embeds IPD checkpoints and technical reviews to govern key milestones; incorporates risk management for prevention, monitoring, and post-analysis. Ultimate Goal: Ensure high-quality project delivery while minimizing potential risks. After: Data-Driven Innovation Strategy Optimization Project Review: Compare project baselines with actual execution to deeply analyze quality, timeline, and cost performance. Deeper Insights: Identify key factors that influence project success. Go-to-Market Tracking: Monitor GMV trends across e-commerce platforms, VOC on social media, and promotional campaign outcomes to pinpoint growth opportunities and risks, driving agile strategy iteration. Advanced Capabilities: Fuel product iteration and innovation, providing a core foundation for the next-generation breakout product. Data Asset Management: Leverages delivery data and gate review points to auto-update master product data, creating a unified view with field supplementation and relationship validation. Long-Term Value: Enables full-lifecycle product data management, enhancing both data quality and business utility. 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