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Riding onboard with Rivian’s race to autonomy | TechCrunch

Riding onboard with Rivian’s race to autonomy | TechCrunch

The robot swerved through the cafeteria of Rivian’s Palo Alto office, shelves adorned with chilled canned coffees — until it didn’t. Five minutes later, a man carefully pushed it out of everyone’s way, the words “I’m stuck” flashing yellow on the poor droid’s screen.

It was an inauspicious start to Rivian’s “Autonomy & AI Day,” a showcase for the company’s plans to make its vehicles capable of driving themselves. Rivian doesn’t make the cafeteria robot and isn’t responsible for its abilities, but there was a familiar message in its foibles: this stuff is hard.

Hours later, as I rode in a 2025 R1S SUV during my 15-minute demo of Rivian’s new self-described “Large Driving Model,” I was reminded of that message.

The EV equipped with the automated-driving software drove myself and two Rivian employees on a switchback route near the company’s campus. As we glided past Tesla’s engineering office, I noticed a Model S in front of us slow to turn into the rival company’s lot. The R1S eventually noticed this, too, braking hard just before the Rivian employee nearly intervened.

During my demo drive, there was one actual disengagement. The employee in the driver’s seat took over as we passed through a one-lane section of road due to some tree-trimming. Minor stuff overall. But it wasn’t not exactly rare either; I spotted multiple other demo rides that had disengagements too.

The rest of the drive went well enough for software that is not ready to be shipped, especially when you consider that Rivian threw out its old rules-based driver assistance system and adopted an end-to-end approach — which is how Tesla developed Full Self-Driving (Supervised). It stopped at stoplights, it handled turns, it slowed for speed bumps, all without programmed rules telling it to do these things.

A quiet pivot in 2021

Image Credits:Rivian

Rivian’s old system “was all very deterministic, and it was all very structured,” CEO RJ Scaringe said in an interview Thursday. “Everything that the vehicle did was the result of a prescribed control strategy written by humans.”

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Scaringe said that when Rivian saw transformer-based artificial intelligence taking off in 2021, he quietly “reconstituted the team and started with a clean sheet and said, let’s design our self-driving platform for an AI-centric world.”

After spending “a lot of time in the basement,” Rivian launched the new ground-up driving software in 2024 on its second-generation R1 vehicles, which use Nvidia’s Orin processors.

Scaringe said it was only recently that his company started to see dramatic progress “once the data started really pouring in.”

Rivian is betting it can train its Large Driving Model (LDM) on fleet data so quickly that it will allow the company to roll out what it calls “Universal Hands-Free” driving in early 2026. That means Rivian owners will be able to take their hands off the wheel on 3.5 million miles of roads in the U.S. and Canada (so long as there are visible painted lines). In the back half of 2026 Rivian will allow “point-to-point” driving, or the consumer version of the demo we received Thursday.

The ‘eyes off’ to ‘hands off’ challenge

By the end of 2026, after Rivian has started shipping its smaller, more affordable R2 SUVs, it will ditch the Nvidia chips and outfit those vehicles with a new custom autonomy computer unveiled Thursday. That computer, plus a lidar sensor, will eventually allow drivers to take their hands and eyes off the road. True autonomy — where a driver doesn’t have to worry about re-taking control of the vehicle — lies well beyond that and will largely depend on how fast Rivian can train its LDM.

This rollout introduces a near-term challenge for Rivian. The new autonomy computer and lidar won’t be ready until months after the R2 goes on sale. If customers want a vehicle that can handle eyes-off driving (or more), they’ll have to wait. But the R2 is a crucial product for Rivian, and the company needs it to sell well — especially in the wake of declining sales of its first-generation vehicles.

“When tech is moving as fast as it is, there’s always going to be some level of obsolescence, and so what we want to do here is to be really direct” about what’s coming, Scaringe said. The early R2s will still get Rivian’s promised “point-to-point” driving, which will be based on the new software and will be hands-off but not eyes-off.

“So [if] you’re buying an R2 and you buy it in the first nine months, it’s just going to be more constrained,” he said. “I think what will happen is some customers will say ‘that matters a lot to me, and I’m going to wait.’ And some will say ‘I want the newest, best things now, and I’m going to get the R2 now, and maybe I’ll trade it in a year or two, and I’ll get the next version later. Fortunately, there’s so much demand backlog for R2 that we think, by being upfront with this, customers can make the decision themselves.”

“In a perfect world, everything times at the same time, but the timeline of the vehicle and the timeline of the autonomy platform are just not perfectly aligned,” he said.

When I first interviewed Scaringe in 2018, before Rivian even showed what its vehicles looked like, he shared a goal that still rattles around my head. He wanted to make Rivian’s vehicles so capable of driving themselves that: “if you go for a hike, and you start at one point and you finish at another point, you have the vehicle meet you at the end of the trail.”

It was the kind of pie-in-the-sky promise about self-driving cars that was all the rage seven years ago, but it stuck with me at least because it was something that felt true to Rivian’s whole brand of aspirational adventure.

Scaringe told me Thursday he still thinks it’s possible for Rivian to enable a use case like that in the next few years. It certainly won’t happen until the company tests and builds its more-capable R2 vehicles, which is at least a year away in a best-case scenario.

“We could [do that]. It’s not been a huge focus,” he said. That could change as the company gets closer to level 4 autonomy, though, since by then the company will have its LDM trained on trickier roads without guiding features like lane lines.

“Then, it becomes a bit of a like, what’s the ODD [operational design domain]? Dirt roads, off road? Easy,” he said. Just don’t expect a Rivian driving itself up Hell’s Gate in Moab.

“We’re not putting any resources into rock crawling autonomously,” he said. “But in terms of getting to the trail head? For sure.”

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#Riding #onboard #Rivians #race #autonomy #TechCrunch


Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re thinking: Hey, didn’t the head of safety at OpenAI just leave?

In fact, it feels like a head of safety at OpenAI is pretty much always leaving. Working in safety leadership—loosely defined—at OpenAI is a little like working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline:

According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese.

What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.”

The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck.

And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts.

#Safety #Leader #OpenAI #Leftai alignment,AI safety,OpenAI">Yet Another Safety Leader at OpenAI Has Left
                Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re thinking: Hey, didn’t the head of safety at OpenAI just leave? In fact, it feels like a head of safety at OpenAI is pretty much always leaving. Working in safety leadership—loosely defined—at OpenAI is a little like working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline:  According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese. What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.”

 The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck.

 And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts.      #Safety #Leader #OpenAI #Leftai alignment,AI safety,OpenAI

working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline:

According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese.

What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.”

The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck.

And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts.

#Safety #Leader #OpenAI #Leftai alignment,AI safety,OpenAI">Yet Another Safety Leader at OpenAI Has LeftYet Another Safety Leader at OpenAI Has Left
                Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re thinking: Hey, didn’t the head of safety at OpenAI just leave? In fact, it feels like a head of safety at OpenAI is pretty much always leaving. Working in safety leadership—loosely defined—at OpenAI is a little like working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline:  According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese. What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.”

 The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck.

 And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts.      #Safety #Leader #OpenAI #Leftai alignment,AI safety,OpenAI

Johannes Heidecke, the Head of Safety Systems at OpenAI, is leaving. I know what you’re thinking: Hey, didn’t the head of safety at OpenAI just leave?

In fact, it feels like a head of safety at OpenAI is pretty much always leaving. Working in safety leadership—loosely defined—at OpenAI is a little like working as a drummer in the band Spinal Tap; lots of turnover. I’m not the world’s premier OpenAI Kremlinologist, so I might be missing some details and nuance, but here’s my basic timeline:

According to Wired, those previously reporting to Heidecke’s safety teams will be led by Mia Glaese, who is a VP, and also the head of alignment. However, there does seem to be an other replacement for Heidecke, according to Wired. Saachi Jain, former leader of safety teams, will now be an “interim head of safety systems” under Glaese.

What exactly keeps happening inside OpenAI’s offices is anyone’s guess, but OpenAI research chief Mark Chen did at least give Wired a hint, saying, “The demands on safety continue to increase—we are training models at a much faster cadence, and release cycles have come down greatly in turn,” and added, “As a result, we have bigger coordination challenges around safety today than ever before.”

The generous reading is that this is still an immature industry. The points along the chain where safety considerations are needed genuinely may keep jumping around as OpenAI figures out how best to build its products. Perhaps today’s sensible safety test procedure is tomorrow’s unnecessary bottleneck.

And there’s no actual direct evidence for a less generous reading of Heidecke’s departure—for instance, one in which any such consideration is a post-hoc rationalization for a pruning of safety procedures in service of faster product rollouts.

#Safety #Leader #OpenAI #Leftai alignment,AI safety,OpenAI

Image may contain Adapter Electronics Escooter Transportation and Vehicle

Photograph: Chris Null

Naturally, the AstroRinse also needs a power supply, so if you don’t have a standard electrical outlet near your hose spigot, you’ll need another extension cord solution here. The unit must be level to run properly, and it features adjustable feet and a built-in spirit level to help you achieve that.

All told, you’ll need to carefully consider where you’re going to place the AstroRinse, ensuring you have access to water, power, and drainage—and that the location isn’t too far from the pool. Since the AquaSense X robot itself weighs 29 pounds (and more when freshly pulled from the water), you probably don’t want to haul the thing halfway across the yard to clean and charge it. Unfortunately, given the availability of the above three services in my backyard, that’s exactly what I had to do.

A Familiar Friend in the Water

The Beatbot AquaSense X robot is nearly identical in appearance to the Beatbot AquaSense 2 Ultra except for some changes to the basket design (which is a single piece here instead of two). Setting it up is far simpler than the AstroRinse.

Physical configuration involves installing two side brushes—these are used only by the skimmer function—but this is a fairly quick affair. Once the brushes are attached, the robot must be set on top of the AstroRinse cleaner so the two devices can be wirelessly paired together. (The quick start guide lays out the particular button presses you must do to complete this process; don’t lose it.) Lastly, the system must then be paired to the Beatbot mobile app; you’ll need Bluetooth and a 2.4 GHz or 5 GHz Wi-Fi connection to complete this task. One tiny hiccup I encountered: After completing all this work, both devices downloaded firmware updates, which promptly broke their pairing connection. It was easy to reestablish, however, by simply repeating the pairing process.

Video: Chris Null

After a full charge, I put the cleaner through its paces in the pool on both the floor and the surface, and as expected, I saw no real difference in performance against the AquaSense 2 Ultra. During floor testing with both organic and synthetic debris, the device picked up an average of 97 percent of the test material, doing exceptionally well on steps and platforms. On the surface, the unit was predictably middling to awful, collecting less than half of floating debris and sinking most of the rest. The unit is just too slow to collect much material on the surface, even though its spinning side brushes help, to a small extent, to pull leaves into its maw.

On the floor of the pool, maximum running time is about 41/2 hours, courtesy of a 13,400 mAh battery—the same as the battery on the AquaSense 2 Ultra.

Image may contain Electronics Mobile Phone Phone and Text

ScreenshotBeatbot app via Chris Null

As with other AquaSense robots, a bevy of operating modes are available in the Beatbot app, letting you choose from dozens of potential combinations of floor, wall, waterline, and surface cleaning, each with up to two runs per zone and with various running times. An AI Quick Mode activates the onboard camera to allow the robot to actively search for debris instead of encountering it randomly; it’s good for a quick clean when there’s not much to pick up but more than you can easily fetch with a net.

Again, not much of this is any different from how the AquaSense 2 Ultra behaves, and aside from the poor surface performance, it works outstandingly well.

Charging and Cleaning

On to the main event: cleanup. After each run, the AquaSense X parked itself at the waterline to await retrieval, and I dutifully lugged it across the pool deck to where I had the AstroRinse station set up. While it can take a little trial and error to get the robot seated in just the right spot, once you do, the cleaning system kicks in automatically within a few seconds.

Video: Chris Null

As the rinsing system starts up, the top-mounted arm swings into place and connects with the mouth the robot uses for surface skimming. Then, a high-pressure stream of water (sounding quite loud) begins blasting from the arm and into the filter basket, which is positioned directly below this opening. The water spray runs uninterrupted for three minutes before the arm swings back and the system shuts off. (A quick mode, which runs for one minute, can also be selected in the app.) After that, the arm retracts and the unit is done. Debris is captured in a net-covered basket built into the base of the cleaning station. Any remaining water drains out through a mesh screen at the very bottom of the unit.

Image may contain Car Transportation and Vehicle

Photograph: Chris Null

#Pool #Robot #Cleans #Pooland #Cleansshopping,review,reviews,robots,home,outdoors">This Pool Robot Cleans the Pool—and Then Cleans ItselfPhotograph: Chris NullNaturally, the AstroRinse also needs a power supply, so if you don’t have a standard electrical outlet near your hose spigot, you’ll need another extension cord solution here. The unit must be level to run properly, and it features adjustable feet and a built-in spirit level to help you achieve that.All told, you’ll need to carefully consider where you’re going to place the AstroRinse, ensuring you have access to water, power, and drainage—and that the location isn’t too far from the pool. Since the AquaSense X robot itself weighs 29 pounds (and more when freshly pulled from the water), you probably don’t want to haul the thing halfway across the yard to clean and charge it. Unfortunately, given the availability of the above three services in my backyard, that’s exactly what I had to do.A Familiar Friend in the WaterThe Beatbot AquaSense X robot is nearly identical in appearance to the Beatbot AquaSense 2 Ultra except for some changes to the basket design (which is a single piece here instead of two). Setting it up is far simpler than the AstroRinse.Physical configuration involves installing two side brushes—these are used only by the skimmer function—but this is a fairly quick affair. Once the brushes are attached, the robot must be set on top of the AstroRinse cleaner so the two devices can be wirelessly paired together. (The quick start guide lays out the particular button presses you must do to complete this process; don’t lose it.) Lastly, the system must then be paired to the Beatbot mobile app; you’ll need Bluetooth and a 2.4 GHz or 5 GHz Wi-Fi connection to complete this task. One tiny hiccup I encountered: After completing all this work, both devices downloaded firmware updates, which promptly broke their pairing connection. It was easy to reestablish, however, by simply repeating the pairing process.Video: Chris NullAfter a full charge, I put the cleaner through its paces in the pool on both the floor and the surface, and as expected, I saw no real difference in performance against the AquaSense 2 Ultra. During floor testing with both organic and synthetic debris, the device picked up an average of 97 percent of the test material, doing exceptionally well on steps and platforms. On the surface, the unit was predictably middling to awful, collecting less than half of floating debris and sinking most of the rest. The unit is just too slow to collect much material on the surface, even though its spinning side brushes help, to a small extent, to pull leaves into its maw.On the floor of the pool, maximum running time is about 41/2 hours, courtesy of a 13,400 mAh battery—the same as the battery on the AquaSense 2 Ultra.ScreenshotBeatbot app via Chris NullAs with other AquaSense robots, a bevy of operating modes are available in the Beatbot app, letting you choose from dozens of potential combinations of floor, wall, waterline, and surface cleaning, each with up to two runs per zone and with various running times. An AI Quick Mode activates the onboard camera to allow the robot to actively search for debris instead of encountering it randomly; it’s good for a quick clean when there’s not much to pick up but more than you can easily fetch with a net.Again, not much of this is any different from how the AquaSense 2 Ultra behaves, and aside from the poor surface performance, it works outstandingly well.Charging and CleaningOn to the main event: cleanup. After each run, the AquaSense X parked itself at the waterline to await retrieval, and I dutifully lugged it across the pool deck to where I had the AstroRinse station set up. While it can take a little trial and error to get the robot seated in just the right spot, once you do, the cleaning system kicks in automatically within a few seconds.Video: Chris NullAs the rinsing system starts up, the top-mounted arm swings into place and connects with the mouth the robot uses for surface skimming. Then, a high-pressure stream of water (sounding quite loud) begins blasting from the arm and into the filter basket, which is positioned directly below this opening. The water spray runs uninterrupted for three minutes before the arm swings back and the system shuts off. (A quick mode, which runs for one minute, can also be selected in the app.) After that, the arm retracts and the unit is done. Debris is captured in a net-covered basket built into the base of the cleaning station. Any remaining water drains out through a mesh screen at the very bottom of the unit.Photograph: Chris Null#Pool #Robot #Cleans #Pooland #Cleansshopping,review,reviews,robots,home,outdoors

Beatbot AquaSense 2 Ultra except for some changes to the basket design (which is a single piece here instead of two). Setting it up is far simpler than the AstroRinse.

Physical configuration involves installing two side brushes—these are used only by the skimmer function—but this is a fairly quick affair. Once the brushes are attached, the robot must be set on top of the AstroRinse cleaner so the two devices can be wirelessly paired together. (The quick start guide lays out the particular button presses you must do to complete this process; don’t lose it.) Lastly, the system must then be paired to the Beatbot mobile app; you’ll need Bluetooth and a 2.4 GHz or 5 GHz Wi-Fi connection to complete this task. One tiny hiccup I encountered: After completing all this work, both devices downloaded firmware updates, which promptly broke their pairing connection. It was easy to reestablish, however, by simply repeating the pairing process.

Video: Chris Null

After a full charge, I put the cleaner through its paces in the pool on both the floor and the surface, and as expected, I saw no real difference in performance against the AquaSense 2 Ultra. During floor testing with both organic and synthetic debris, the device picked up an average of 97 percent of the test material, doing exceptionally well on steps and platforms. On the surface, the unit was predictably middling to awful, collecting less than half of floating debris and sinking most of the rest. The unit is just too slow to collect much material on the surface, even though its spinning side brushes help, to a small extent, to pull leaves into its maw.

On the floor of the pool, maximum running time is about 41/2 hours, courtesy of a 13,400 mAh battery—the same as the battery on the AquaSense 2 Ultra.

Image may contain Electronics Mobile Phone Phone and Text

ScreenshotBeatbot app via Chris Null

As with other AquaSense robots, a bevy of operating modes are available in the Beatbot app, letting you choose from dozens of potential combinations of floor, wall, waterline, and surface cleaning, each with up to two runs per zone and with various running times. An AI Quick Mode activates the onboard camera to allow the robot to actively search for debris instead of encountering it randomly; it’s good for a quick clean when there’s not much to pick up but more than you can easily fetch with a net.

Again, not much of this is any different from how the AquaSense 2 Ultra behaves, and aside from the poor surface performance, it works outstandingly well.

Charging and Cleaning

On to the main event: cleanup. After each run, the AquaSense X parked itself at the waterline to await retrieval, and I dutifully lugged it across the pool deck to where I had the AstroRinse station set up. While it can take a little trial and error to get the robot seated in just the right spot, once you do, the cleaning system kicks in automatically within a few seconds.

Video: Chris Null

As the rinsing system starts up, the top-mounted arm swings into place and connects with the mouth the robot uses for surface skimming. Then, a high-pressure stream of water (sounding quite loud) begins blasting from the arm and into the filter basket, which is positioned directly below this opening. The water spray runs uninterrupted for three minutes before the arm swings back and the system shuts off. (A quick mode, which runs for one minute, can also be selected in the app.) After that, the arm retracts and the unit is done. Debris is captured in a net-covered basket built into the base of the cleaning station. Any remaining water drains out through a mesh screen at the very bottom of the unit.

Image may contain Car Transportation and Vehicle

Photograph: Chris Null

#Pool #Robot #Cleans #Pooland #Cleansshopping,review,reviews,robots,home,outdoors">This Pool Robot Cleans the Pool—and Then Cleans Itself
Image may contain Adapter Electronics Escooter Transportation and Vehicle

Photograph: Chris Null

Naturally, the AstroRinse also needs a power supply, so if you don’t have a standard electrical outlet near your hose spigot, you’ll need another extension cord solution here. The unit must be level to run properly, and it features adjustable feet and a built-in spirit level to help you achieve that.

All told, you’ll need to carefully consider where you’re going to place the AstroRinse, ensuring you have access to water, power, and drainage—and that the location isn’t too far from the pool. Since the AquaSense X robot itself weighs 29 pounds (and more when freshly pulled from the water), you probably don’t want to haul the thing halfway across the yard to clean and charge it. Unfortunately, given the availability of the above three services in my backyard, that’s exactly what I had to do.

A Familiar Friend in the Water

The Beatbot AquaSense X robot is nearly identical in appearance to the Beatbot AquaSense 2 Ultra except for some changes to the basket design (which is a single piece here instead of two). Setting it up is far simpler than the AstroRinse.

Physical configuration involves installing two side brushes—these are used only by the skimmer function—but this is a fairly quick affair. Once the brushes are attached, the robot must be set on top of the AstroRinse cleaner so the two devices can be wirelessly paired together. (The quick start guide lays out the particular button presses you must do to complete this process; don’t lose it.) Lastly, the system must then be paired to the Beatbot mobile app; you’ll need Bluetooth and a 2.4 GHz or 5 GHz Wi-Fi connection to complete this task. One tiny hiccup I encountered: After completing all this work, both devices downloaded firmware updates, which promptly broke their pairing connection. It was easy to reestablish, however, by simply repeating the pairing process.

Video: Chris Null

After a full charge, I put the cleaner through its paces in the pool on both the floor and the surface, and as expected, I saw no real difference in performance against the AquaSense 2 Ultra. During floor testing with both organic and synthetic debris, the device picked up an average of 97 percent of the test material, doing exceptionally well on steps and platforms. On the surface, the unit was predictably middling to awful, collecting less than half of floating debris and sinking most of the rest. The unit is just too slow to collect much material on the surface, even though its spinning side brushes help, to a small extent, to pull leaves into its maw.

On the floor of the pool, maximum running time is about 41/2 hours, courtesy of a 13,400 mAh battery—the same as the battery on the AquaSense 2 Ultra.

Image may contain Electronics Mobile Phone Phone and Text

ScreenshotBeatbot app via Chris Null

As with other AquaSense robots, a bevy of operating modes are available in the Beatbot app, letting you choose from dozens of potential combinations of floor, wall, waterline, and surface cleaning, each with up to two runs per zone and with various running times. An AI Quick Mode activates the onboard camera to allow the robot to actively search for debris instead of encountering it randomly; it’s good for a quick clean when there’s not much to pick up but more than you can easily fetch with a net.

Again, not much of this is any different from how the AquaSense 2 Ultra behaves, and aside from the poor surface performance, it works outstandingly well.

Charging and Cleaning

On to the main event: cleanup. After each run, the AquaSense X parked itself at the waterline to await retrieval, and I dutifully lugged it across the pool deck to where I had the AstroRinse station set up. While it can take a little trial and error to get the robot seated in just the right spot, once you do, the cleaning system kicks in automatically within a few seconds.

Video: Chris Null

As the rinsing system starts up, the top-mounted arm swings into place and connects with the mouth the robot uses for surface skimming. Then, a high-pressure stream of water (sounding quite loud) begins blasting from the arm and into the filter basket, which is positioned directly below this opening. The water spray runs uninterrupted for three minutes before the arm swings back and the system shuts off. (A quick mode, which runs for one minute, can also be selected in the app.) After that, the arm retracts and the unit is done. Debris is captured in a net-covered basket built into the base of the cleaning station. Any remaining water drains out through a mesh screen at the very bottom of the unit.

Image may contain Car Transportation and Vehicle

Photograph: Chris Null

#Pool #Robot #Cleans #Pooland #Cleansshopping,review,reviews,robots,home,outdoors

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