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A robot vacuum maps its surroundings to help it avoid running into obstacles and efficiently navigate. This technology is similar to the one used in self-driving cars and aerospace.

Simple robots come with bump sensors that prevent them from scratching your chair's legs or scuffing your paint. But more sophisticated navigation systems, such as Lidar and SLAM, are better in avoiding accidents that aren't planned. But this kind of technology can increase the cost.

Lidar

The most significant advancement in robot vacuums for the last decade has been lidar, or light detection and the ability to range. Lidar is a sensor which sends laser beams out and tracks the time it takes to return them. The information can be used to create maps that are precise. Lidar makes it easier for robots to avoid and navigate around objects particularly in dim lighting.

Even though most modern robotic vacuums feature some kind of obstacle detection but they struggle to untangle socks, cords and other household items that easily get caught on the floor. A weak obstacle detection system could seriously affect the cleaning efficiency of a robot vacuum and cause lots of wasted time. You will have to stop it and manually detangle any object is tangled.

The top robotic vacuums that use lidar have powerful object detection abilities that will ensure that your floors are kept clean and free from debris and tangles. You'll also find that these vacuums are less likely to get stuck on furniture legs or other things that are common obstacles in narrow hallways and spaces that are narrow.

Certain robots equipped with lidar feature digital keep-out zones, that allow you to draw a virtual boundary on the map to stop the robovac from cleaning certain areas of your house or apartment. This will stop your vacuum from accidentally sweeping the cat litter box or an expensive area rug.

Another benefit of a robot with lidar explained is the ability to better identify stairs. While getting a robot to climb the stairs is a challenging task, many models with lidar are able climb them without difficulty.

Other sensors you might need to look for in a robotics system with lidar include infrared sensors which are used to detect furniture and walls and help it navigate the surrounding; 3D ToF sensors, which use reflective infrared light to find objects and calculate their location; and cliff sensors, that alert the vac when it gets too close to the edge of a staircase, to prevent it from falling off.

Gyroscopes

In contrast to lidar, which employs lasers to scan the space and map it out, gyroscopes depend on sensors that rotate to prevent the robot from bumping into things. These are more common in budget robots, and they work as quick-spinning wheel that lets the vacuum know where it is relative to obstacles. Some models utilize gyroscopes order to create the home map. This is helpful to ensure that the space is cleaned thorough and keeping track of the area.

SLAM which stands for Simultaneous Localization and Mapping, is another well-known navigation technology for robot vacuums that's available across different price points. This technique is utilized to create a 3-D image of your room to allow the robot to create a precise map and navigate around it in a rational manner. This is a significant improvement over the bounce-and-bang machines of the past that simply plow through your room, bouncing off whatever they encountered until the job was completed.

In addition to forming maps, the majority of robots that make use of SLAM can display them in an app so you can know where your cleaner is at any time. You can also create no-go zones based on maps. This is particularly helpful for homes with lots of furniture, since it can be difficult to know what's where without a home map.

SLAM is effective for many situations, however it's not as effective at detecting smaller objects, like wires or cables that could be caught up by the brush that rotates in the vacuum robot with lidar. This is a major shortcoming because robots are susceptible to take on these objects and causing harm.

Fortunately, the majority robots that use SLAM are equipped with obstacles detection and drop detectors technology. These sensors keep the vacuum from falling down stairs or other huge differences in flooring levels that could cause severe damage. Some robots also have cliff sensors, which could be beneficial if you have animals that leap over the robot to get its water or food dish. These sensors are typically located on the vac's bumpers and emit signals when the vac is within range of something that might hurt it.

Wall Sensors

The ability of a robot vacuum to navigate your home is dependent on combination sensors. A budget model might make use of bump sensors to detect obstacles and a light that rotates to detect walls, but higher-end models are far more advanced, with self-navigation, mapping and self-navigation systems that allow for map saving (with some retaining or transmitting the data to a company) and digital keep-out zones to prevent robots from accidentally damaging cables or knocking down furniture legs.

Some robots use SLAM or simultaneous localization mapping. They will map the room prior to when they begin cleaning, and will refer to this map throughout the entire process. This makes them a lot more efficient, as they know exactly where they've been, and can avoid repeating the same sections of the room. It is also possible to view and share these maps within the cheapest robot vacuum with lidar's application, which is a great feature if prefer to set up areas that are not allowed to be entered or clean up by the area.

The other important navigation sensor you'll want to look for is the gyroscope. Gyroscopes rely on spinning wheels or a quickly-rotating beam of light to determine the distance between your robot and obstacles within your home. They use this information to create a virtual map that the bot can reference when it moves through your space. Without this technology, robots can become entangled with things like cords and rugs and can zig-zag across the floor rather than following the edges of rooms.

The most efficient robots are equipped with a variety of different obstacle avoidance technologies, which could include 3D structured light, 3D ToF (time of flight) monocular or binocular vision-based LiDAR. The more advanced the technology, the more precise and effective your robot's navigation will be. This translates into more thorough, low-maintenance clean ups and the option of setting up no-go zones to protect your electronics and other valuables from damage caused by accidents. The most recent generation of gyroscopes which are more precise and operate well in low-light, will even detect a change in ambient lighting in your home to help the robot see more effectively.

Optical Sensors

A robot vacuum equipped with lidar can create an 3D map of your environment to help you better navigate and avoid hitting obstacles. It accomplishes this by sending out a laser beam that bounces off surfaces and then returns to the sensor. The sensor is able to measure the time taken for the laser beam to return. This is converted into distance measurements, and allows the robot build up a picture about the arrangement of your room.

As opposed to cameras, which are used in certain robots to map rooms, lidar is more efficient and more accurate. A robot with lidar could have the "no go" zone feature. This allows you to define areas where your robot is not allowed. In our tests we found the top models that utilize this technology to be Neato Botvac D8 and iRobot Braava 450, both of which have easy-to-set-up "no-go" zones within the app.

The iRobot Duo+ is another great option that uses LiDAR as well as other sensors to create an precise map of your home, which it will be used for navigation. The app also gives you control over the mapping process so you can refine your home's boundaries if necessary.

Other technologies that are used to improve robot navigation include 3D structured lights, which measure distances by the detection of reflective properties of objects and 3D TOF (time-of-flight) which scans an area to measure the speed of light reflections and their direction. Some robots also utilize monocular and binocular vision to identify objects and avoid them.