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Most Robot Vacuum cleaners today will not fall down the stairs.
This is because of the inbuilt lidar, laser, infrared or ultrasonic sensors.
Most robot vacuums use ultrasonic sensors for object detection and cliff detection.
An ultrasonic sensor is a sensor that sends out soundwaves and these soundwaves bounce back into a receiver.
The time it takes for a soundwave to bounce back determines the distance to the object.
You cannot hear the sound an ultrasonic sensor produces because it’s produced in a very high frequency above the human hearing capability.
You’ll also typically hear of an infrared cliff detector, which works with the same principle just with a specific wavelength of light rather than sound.
Infrared is very precise and quick when the distance to the object is small, but the infrared light fades out quickly and will be more imprecise the longer the distance.
For robot vacuums, an infrared sensor should be more than plenty.
Then the ultrasonic sensor detects a fall of over 1 cm. It’ll send a signal to the robot vacuum to stop and/or change direction depending on the situation and surroundings.
Robot vacuums with mapping capability will also remember the staircase. On the map, it’ll probably just look like a wall, so it knows that it cannot go there.
This works very well and you can easily test it out yourself.
A cliff detection sensor is a safety requirement in vacuum robots today, and therefore if you buy a new robot vacuum it should have one installed.
But if you buy a used robot vacuum you have to be sure that it has a cliff detection, because this was not a standard in the earlier robot vacuums.
Depending on what model of robot vacuum you are using, there are several factors that the reliability will depend on. In general, yes the cliff detectors can be trusted and relied on.
To make sure the cliff detection are properly working all the time, you should make sure that all dust are cleaned away from the sensor.
If too much dust is covering the infrared sensors the light has trouble getting through and bounce back.
In a situation like this, the infrared sensors cannot signal the robot vacuum that it is near a cliff or a drop and it then won’t stop.
Infrared sensors can also have issues with dark grey or black floors, especially if it’s a very dark carpet.
The darkness will absorb much of the light and almost none with getting reflected back into the receiver.
In some cases, if the floor or carpet is dark enough it’ll perceive the darkness as drops and it’ll then go around these dark surfaces.
The infrared cliff sensors work optimally on lighter and blank surfaces which can easily reflect light.
Carpets that are too rough can also be an issue even if they aren’t dark, so keep this in mind before buying a robot vacuum.
If you don’t have a staircase or any large drops, you could actually just tape over the infrared sensors.
This will make your robot vacuum ignore any drops and it’ll try to go over any surface.
But if you do this and you have a staircase, it’ll for sure fall down the stairs. So I do not recommend doing this unless you have to.
If you have to do it, use a light tape that reflects light easily, if you use dark tape it’ll not go anywhere.
The first step is to read the manual and find the placement of the sensor. Down below is a picture of a Neato robot vacuum and the placement of its infrared sensors.
After you’ve located the sensors through the manual, turn off the robot vacuum and turn it around.
For this Neato model above the sensors are located in the front on each side of the robot. You can then take a cotton swab or a thin piece of cloth and lightly clean the sensor windows.
Make sure to not push it too hard, it’s fragile glass or plastic if it’s broken the infrared may stop working.
Make sure to always read the manual, it’s not sure you even have an infrared sensor, it might be an ultrasonic sensor which will not have to be cleaned.
Morten has been working with technology, IoT and electronics for over a decade. His passion for technology is reflected into this blog to give you relevant and correct information.Read more...