Wednesday, October 27

Robot vacuum cleaner or AI vacuum cleaner How are they different? | Digital Trends Spanish


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If you have been looking to buy a robot vacuum cleaner, there is a chance that you will stumble upon some keywords that illustrate how these devices leave our homes so clean. Beyond the phrases we all know as “suction power”, “filtration”, and “mobile app”, a fashionable expression in the world of vacuum cleaners that appears more in the foreground these days is “artificial intelligence” (AI ); that is why here we are going to help you decide what is best for you, robot vacuum cleaner or AI vacuum cleaner. Read on and discover their differences.

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Robot vacuum cleaner or AI vacuum cleaner How are they different?

How does an AI vacuum cleaner work?

There’s a lot of science going into the basics of AI vacuums, but we’re going to focus on some of the surface-level technologies that give these robots their distinctive performance advantages (and high prices).

When you take an AI vacuum cleaner out of its packaging, one of the first things you’ll have to do is sync it with your home Wi-Fi network. So, you are going to want to download the associated app that you will use to control and customize the vacuum cleaner. After taking it out and plugging it in, the AI ​​vacuum cleaner will carefully scan your home, creating a “vacuum map” that your device will use as a reference when cleaning. The same map will also be available for you to examine and manipulate in the vacuum cleaner’s mobile app.

An AI vacuum cleaner makes a detailed cleaning plan using one of two mapping methods: a laser-guided scan of your residence, known as Lidar (Light Detection and Ranging), or a camera-centric scan called vSLAM (Visual Simultaneous Localization and Mapping).

When you are buying such a device, you may have noticed a bulge on the upper outer part of various brands of robot vacuum cleaners (like the Xiaomi Roidmi model above) and / or a camera lens somewhere on the main body of the vacuum cleaner. . The first is a lidar laser cage, and the second is a vSLAM camera.

How is an AI vacuum cleaner different from a robot vacuum cleaner?

In the early days of robot vacuum cleaners, and continuing to the most basic robot models today, these robots were designed with basic sensors and one or two key algorithms to help the vacuum cleaner navigate the home. If you’ve ever seen an inexpensive robot in action, you know that these robots rely heavily on trial and error as it maneuvers around your house. Once you activate a basic robot, it will glide across the floor, capturing as much dust as it can … until it bumps into a piece of furniture.

Although the rubber-covered edges of many robot vacuums help prevent any serious damage to furniture in your home, the device’s sensors are typically only smart enough to tell the vacuum cleaner when it is bumping into something. You may even have to move your robot when it’s in a tight spot. This is where the power and precision of an AI vacuum cleaner come into play.

An AI vacuum cleaner combines the above-mentioned map scans with object identification and learning algorithms to make the robot vacuum experience faster, more thorough, and safer.

Lidar and vSLAM mapping: safer and better cleaning

Although there are basic sensors built into these robots for contact avoidance purposes, the Lidar and vSLAM mappings give your vacuum cleaner an elaborate benchmark when cleaning. In fact, you should know that AI vacuums tend to clean your house faster and in straighter lines compared to some of the more circular sweeping maneuvers of basic robot models.

Additionally, deep learning and object identification let your AI vacuum cleaner know what to avoid when vacuuming. The loops and power cables sucked by your robot are in the past.

Bottom line: an AI vacuum cleaner uses mapping and adaptive learning technologies to tell your robot what to clean, where to clean, and when to clean. Although sensors and algorithms are not completely absent from many of today’s robot vacuums, the low and medium quality models typically do not come with the intuitive learning tools of the more advanced AI models.

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