Tech
Teaching robots to map large environments
A robot searching for workers trapped in a partially collapsed mine shaft must rapidly generate a map of the scene and identify its location within that scene as it navigates the treacherous terrain.
Researchers have recently started building powerful machine-learning models to perform this complex task using only images from the robot’s onboard cameras, but even the best models can only process a few images at a time. In a real-world disaster where every second counts, a search-and-rescue robot would need to quickly traverse large areas and process thousands of images to complete its mission.
To overcome this problem, MIT researchers drew on ideas from both recent artificial intelligence vision models and classical computer vision to develop a new system that can process an arbitrary number of images. Their system accurately generates 3D maps of complicated scenes like a crowded office corridor in a matter of seconds.
The AI-driven system incrementally creates and aligns smaller submaps of the scene, which it stitches together to reconstruct a full 3D map while estimating the robot’s position in real-time.
Unlike many other approaches, their technique does not require calibrated cameras or an expert to tune a complex system implementation. The simpler nature of their approach, coupled with the speed and quality of the 3D reconstructions, would make it easier to scale up for real-world applications.
Beyond helping search-and-rescue robots navigate, this method could be used to make extended reality applications for wearable devices like VR headsets or enable industrial robots to quickly find and move goods inside a warehouse.
“For robots to accomplish increasingly complex tasks, they need much more complex map representations of the world around them. But at the same time, we don’t want to make it harder to implement these maps in practice. We’ve shown that it is possible to generate an accurate 3D reconstruction in a matter of seconds with a tool that works out of the box,” says Dominic Maggio, an MIT graduate student and lead author of a paper on this method.
Maggio is joined on the paper by postdoc Hyungtae Lim and senior author Luca Carlone, associate professor in MIT’s Department of Aeronautics and Astronautics (AeroAstro), principal investigator in the Laboratory for Information and Decision Systems (LIDS), and director of the MIT SPARK Laboratory. The research will be presented at the Conference on Neural Information Processing Systems.
Mapping out a solution
For years, researchers have been grappling with an essential element of robotic navigation called simultaneous localization and mapping (SLAM). In SLAM, a robot recreates a map of its environment while orienting itself within the space.
Traditional optimization methods for this task tend to fail in challenging scenes, or they require the robot’s onboard cameras to be calibrated beforehand. To avoid these pitfalls, researchers train machine-learning models to learn this task from data.
While they are simpler to implement, even the best models can only process about 60 camera images at a time, making them infeasible for applications where a robot needs to move quickly through a varied environment while processing thousands of images.
To solve this problem, the MIT researchers designed a system that generates smaller submaps of the scene instead of the entire map. Their method “glues” these submaps together into one overall 3D reconstruction. The model is still only processing a few images at a time, but the system can recreate larger scenes much faster by stitching smaller submaps together.
“This seemed like a very simple solution, but when I first tried it, I was surprised that it didn’t work that well,” Maggio says.
Searching for an explanation, he dug into computer vision research papers from the 1980s and 1990s. Through this analysis, Maggio realized that errors in the way the machine-learning models process images made aligning submaps a more complex problem.
Traditional methods align submaps by applying rotations and translations until they line up. But these new models can introduce some ambiguity into the submaps, which makes them harder to align. For instance, a 3D submap of a one side of a room might have walls that are slightly bent or stretched. Simply rotating and translating these deformed submaps to align them doesn’t work.
“We need to make sure all the submaps are deformed in a consistent way so we can align them well with each other,” Carlone explains.
A more flexible approach
Borrowing ideas from classical computer vision, the researchers developed a more flexible, mathematical technique that can represent all the deformations in these submaps. By applying mathematical transformations to each submap, this more flexible method can align them in a way that addresses the ambiguity.
Based on input images, the system outputs a 3D reconstruction of the scene and estimates of the camera locations, which the robot would use to localize itself in the space.
“Once Dominic had the intuition to bridge these two worlds — learning-based approaches and traditional optimization methods — the implementation was fairly straightforward,” Carlone says. “Coming up with something this effective and simple has potential for a lot of applications.
Their system performed faster with less reconstruction error than other methods, without requiring special cameras or additional tools to process data. The researchers generated close-to-real-time 3D reconstructions of complex scenes like the inside of the MIT Chapel using only short videos captured on a cell phone.
The average error in these 3D reconstructions was less than 5 centimeters.
In the future, the researchers want to make their method more reliable for especially complicated scenes and work toward implementing it on real robots in challenging settings.
“Knowing about traditional geometry pays off. If you understand deeply what is going on in the model, you can get much better results and make things much more scalable,” Carlone says.
This work is supported, in part, by the U.S. National Science Foundation, U.S. Office of Naval Research, and the National Research Foundation of Korea. Carlone, currently on sabbatical as an Amazon Scholar, completed this work before he joined Amazon.
Tech
I Tested Garmin Watches for a Decade While Hiking, Biking, and Climbing. Here’s What You Should Buy
Last year, Garmin introduced a Pro version that incorporates the inReach’s satellite communications savvy. Not only does it cost at least $400 more than the Apple Watch Ultra and $200 more than the regular Fenix 8, but you also have to pay for the inReach subscription plan, which has several tiers and ranges from $8/month to $50/month depending on whether you want features like unlimited texting or sending photo messages.
What you get for this mind-boggling price is a sports watch that can do anything and everything. It has best-in-class battery life (every Fenix can last for weeks on a single charge, and up to a month with solar charging) and features like the depth sensor from Garmin’s Descent line, which means this watch works as a full-on dive computer for scuba and free diving. It has a microphone and speaker for basic voice commands (although no onboard cellular connectivity), the surprisingly useful built-in LED flashlight, and Garmin’s signature built-in topographic maps, 24/7 health monitoring, and tracking for over a hundred different activities.
I’ve taken the 51-mm version on pretty much every outdoor sport—snowboarding, trail running, mountain biking, and rock climbing. Every time I use it, its capabilities far outclass my own. I have irritated many a fellow climber by attempting to track route difficulty, duration, and falls while integrating my Body Battery metrics and so on. The danger is always that you’ll spend more time fiddling with your Garmin Fenix 8 than you do with your actual sport. I have the version with the sapphire glass face and the titanium bezel, and have smashed it into rock faces with nary a scratch. If you’re up for paying the price and want a good-looking watch that will last forever (I have friends who are still wearing their Fenix 5s and 6s, and honestly, they’re fine), this is the one to get.
Best Running Watch
The Garmin Forerunner series launched in the early 2000s and has become the quintessential runner’s watch. Like all Garmins, the Forerunner comes in a range of price points, each offering different features. Last year, Garmin released the Forerunner 570 ($550), a midrange model with no LED flashlight or onboard maps, and the Forerunner 970 ($750), which is the premium version. Before I go into detail about why the Forerunner 970 is the best option, I should also say that I have tested many previous Garmin Forerunners at various price points. If you’re not a triathlete, the older Forerunners are still worth considering, and the entry-level $200 Forerunner 165 is aimed explicitly at runners, instead of including triathletes as the more expensive models do.
Tech
Save Up to 40% With These Acer Promo Codes and Discounts
Acer is one of the top largest PC manufacturers in the world, perhaps best known for its gaming line and budget-friendly options. If you’ve already got your eye on an Acer product like a laptop or monitor, and are shopping at the company’s online storefront, you should be using one of these Acer promo codes and coupons to save some cash on your purchase.
Save 40% on Accessories When You Build an Acer Bundle
If you’re buying from Acer, you’re most likely shopping for either a desktop PC or laptop. With this discount, you can get a really solid deal on accessories if you bundle it with a mouse, laptop bag, or headset. When you go to purchase a PC, just click “Build Bundle” and you’ll see some of the eligible options, all of which are reduced by 40%. The Nitro Mechanical Keyboard, for example, goes from $50 to just $30. That 40% is a real discount, too, as that same keyboard costs $50 on Amazon when I checked.
Beyond peripheral add-ons, you can also save 10% off Acer Care Plus extended service plans or McAfee LiveSafe antivirus subscriptions. You can bundle up to five products together to save the most money. If you’re headed off to college (or have a kid in the family), a bundle like this can get you everything you need for a gaming or studying setup on the go.
Shop Rotating Weekly Deals on Monitors and Gaming Gear
Acer’s PC gaming offerings come in either the flagship Predator brand or the budget-tier Nitro. Acer offers rotating weekly deals on everything from monitors to gaming laptops, some of which are my favorites that I’ve tested in their given category. The Acer Nitro V 16, for example, was a budget gaming laptop that I recommended quite a lot last year because of its incredible price. The one I tested was the entry-level version with an Nvidia RTX 5050 inside, but Acer has the RTX 5060 model in its own storefront. It’s $100 off right now at $1,200, which comes with 16 GB of RAM and a terabyte of storage. In fact, it’s only $30 more than the RTX 5050 model, despite offering a significant jump in gaming performance. These discounts are reflected right on the product pages, so there’s no promo code, discount code, or coupon code required.
Acer has a wide selection of monitors available, too, whether that’s a massive 49-incher or a more modest 27-inch gaming workhorse. One of my favorite discounts I saw right now was the Acer Nitro XV2, a 27-inch 1440p display with a 300 Hz refresh rate. It’s 44% off at the time of writing, bringing the price down to just $250. Because these discounts are swapped out on a weekly basis, it’s worth checking back to see if the product you’re eyeing has a new discount.
Select Customers Can Get 15% Off Their Purchase
Acer also offers a number of added discounts at checkout, including 15% off for students. Students will need to verify through Student Beans or SheerID. Because a lot of the devices Acer offers are budget-friendly, they can be attractive for students, and the extra 15% off is the icing on the cake.
We tested the Acer Swift 16 AI last year and really enjoyed the high-resolution, OLED screen and impressively quiet performance. Acer has the smaller version of this same laptop available, the Swift 14 AI, which is currently $150 off. You also might check out the Acer Chromebook Plus 514, a laptop we liked quite a bit when we reviewed it in 2024.
Acer offers this same 15% discount for active duty military, veterans, and their families. It also applies to healthcare professionals, which can be verified through its healthcare discount portal.
Tech
AI Research Is Getting Harder to Separate From Geopolitics
The world’s top AI research conference, the Conference on Neural Information Processing Systems—better known as NeurIPS—became the latest organization this week to become embroiled in a growing clash between geopolitics and global scientific collaboration. The conference’s organizers announced and then quickly reversed controversial new restrictions for international participants after Chinese AI researchers threatened to boycott the event.
“This is a potential watershed moment,” says Paul Triolo, a partner at the advisory firm DGA-Albright Stonebridge who studies US-China relations. Triolo argues that attracting Chinese researchers to NeurIPS is beneficial to US interests, but some American officials have pushed for American and Chinese scientists to decouple their work—especially in AI, which has become a particularly sensitive topic in Washington.
The incident could deepen political tensions around AI research, as well as dissuade Chinese scientists from working at US universities and tech companies in the future. “At some level now it is going to be hard to keep basic AI research out of the [political] picture,” Triolo says.
In its annual handbook for paper submissions, issued in mid-March, NeurIPS organizers announced updated restrictions for participation. The rules stated that the event could not provide services including “peer review, editing, and publishing” to any organizations subject to US sanctions, and linked to a database of sanctioned entities. It included companies and organizations on the Bureau of Industry and Security’s entity list and those on another list with alleged ties to the Chinese military.
The new rules would have affected researchers at Chinese companies like Tencent and Huawei who regularly present work at NeurIPS. The database also includes entities from other countries such as Russia and Iran. The US places limits on doing business with these organizations, but there are no rules around academic publishing or conference participation.
The NeurIPS handbook has since been updated to specify that the restrictions apply only to Specially Designated Nationals and Blocked Persons, a list used primarily for terrorist groups and criminal organizations.
“In preparing the NeurIPS 2026 handbook, we included a link to a US government sanctions tool that covers a significantly broader set of restrictions than those NeurIPS is actually required to follow,” the event’s organizers said in a statement issued Friday. “This error was due to miscommunication between the NeurIPS Foundation and our legal team.”
Before they reversed course, the conference organizers initially said that the new rule was “about legal requirements that apply to the NeurIPS Foundation, which is responsible for complying with sanctions,” adding that it was seeking legal consultation on the issue.
Immediate Backlash
The new rule drew swift backlash from AI researchers around the world, particularly in China, which produces a large quantity of cutting-edge machine learning papers and is home to a growing share of the world’s top AI talent. Several academic groups there issued statements condemning the measure and, more importantly, discouraging Chinese academics from attending NeurIPS in the future. Some urged Chinese academics to contribute instead to domestic research conferences, potentially helping increase the country’s influence in relevant science and tech fields.
The China Association of Science and Technology (CAST), an influential government-affiliated organization for scientists and engineers, said Thursday that it would stop providing funding for Chinese scholars traveling to attend NeurIPS and would use the money instead to support domestic and international conferences that “respect the rights of Chinese scholars.”
CAST also said it will no longer count publications at the 2026 NeurIPS conference as academic achievements when evaluating future research funding. It’s unclear if the organization will reverse course now that NeurIPS has walked back the new rule.
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