To recommend each robot vacuum that we consider, it passes through our test lab in Kentucky’s Louis Will. In addition to the test floor where we run our controlled pickup tests, we monitor each robot vacuum that is full of fun furniture in a special test room to estimate how well it navigates around ordinary barriers. In the past, we examine the ability to sprinkle the hair of every robot vacuum or leave the loose standing behind, we consider moping abilities, and we test to see how well it navigates the fake dog dirt.
Let’s start a little deep into important reservations, starting with our performance tests.
Robot vacuum pickup power
When it comes to emptying, we want to know how effective each robot is against ordinary pieces and other debris, and also how it is fare against small particles like dust, dirt and sand. Learn to know, we use sand as an analog for fine particles.
In each case, we disperse a controlled amount on the three test floors: low pile carpet, midpile carpet and wood floors. Low pile carpet is small, low plush carpet with low fibers, so usually the robot vacuum is an easy time to lift it (though not always). The midpile is soft, more plush carpet with soft, long fibers. This robot is more challenged by vacuum (though again, not always). After that, we take the robot vacuum, empty its dust cans well, send it to clean the affected area, and eventually measure the weight of what he succeeds in lifting. This gives us one eight percent of the entire amount. From there, we repeat each run twice and the average results.
In recent months, we have finished our tests for black rice on hard wood floors, since almost every robot vacuum we tested was scoring close to 100 %. Now we use sand tests as our basic standard in evaluating cleaning performance. We consider anything above 50 % and above a good score of sand.
Robot Vacuum Navigation Skills
Your robot vacuum will clean your home as well as it is capable of visiting it. The ideal cleaner will be easy to find your way from the room to the room and to automatically avoid obstacles, all of which make up for proper, low -maintenance automatic cleaning.
We make sure to observe every robot vacuum because it becomes clear to get a good sense that it is to get the best comparison with the cleaner to the cleaner, we take every one of the long exposure shots because it cleanses our dark test room, which is above the glue sticks. The images that show us light trails that show the path of the robot because it wanders the room and cleanses around our fun furniture.
Below is an example of the Ecovics de Boat T30s, which is the best of our overall. It offers coverage of a wonderful area and performed the navigation very organized and effectively. In the navigation score, he got 10 out of 10, which only takes 15 minutes to complete the cleaning cycle.
On the contrary, we have a robot vacuum that has bad navigation, nosis Floro. It exempts several places in the room, and the lightpath test image contains some bright spots, which possibly indicate that the robot vacuum has spent time to rotate. It is noteworthy that the most unorganized navigation is a model. All this resulted in poor navigation scores.
In large parts, it comes to the game. Over the years, we have permanently noted that the robot vacuum that uses laser guided leather navigation are very good at mapping their environment and finding a way around them. Meanwhile, 3D mapping camera with the object -identified smart can provide the robot vacuum to identify and adjust the obstacles to their path.
