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LiDAR and vSLAM are two of the most popular navigation methods used today the best robot vacuum cleaners. Working in conjunction with different sensors, they help the the robot vacuum cleaner finds its way around your house. They start by creating an initial map of the space, and then help with navigation on cleaning runs. Good navigation ensures that your bot cleans your entire plan – no missed points – efficiently.
LiDAR, or light detection and variation, uses pulses of light sent from an elevated central puck to create a detailed map of an area. It’s probably the most popular navigation method for newer robovacs, and it’s super-accurate and fast. vSLAM – visual simultaneous location and mapping – relies on visual information from the camera to understand the space. It is typically slower and less efficient than LiDAR.
There are also other mapping technologies available, although LiDAR and vSLAM are the most common. Some robovacs will combine multiple mapping technologies together; LiDAR bots still typically have a camera next to their navigation puck.
Here is the short explanation; Now let’s find out exactly how LiDAR and vSLAM compare…
What is LiDAR?
LiDAR is used by most high-end robot vacuum cleaners. This method uses lasers to measure distances and create a precise and accurate image of an area, and is used for initial mapping and general navigation. Here’s how it works:
- A group of light beams are sent from a raised puck located in the center of the upper surface of the robot.
- It uses a ToF (time of flight) sensor to measure how long it takes these rays to return.
- This information is used to find out how distant objects in the area are located.
- All data is collected and used to create a 360-degree map of the room and everything in it.
Pros and cons of LiDAR
As for the current popular robovac navigation methods, LiDAR is the the fastest and more reliable. LiDAR-based robot vacuum cleaners can be expected to navigate clean lines, to ensure they don’t miss spots, and won’t frequently bump into your furniture. In most cases, you’ll be able to watch a visualization of your bot making its way around your home in real time through a companion app.
LiDAR exhibits a few disadvantages. One is that this method relies on an elevated puck, which makes the robovac higher than it would otherwise be. The smaller your bot, the more ground it will cover around your house – that raised puck could be the difference between the robovac being able to clean under your couch, for example.
At the time of writing, Roborock is about to launch a bot that he has a puck that can pop up and down; but otherwise, we haven’t really seen any innovations to counter the problem.
There are also a couple of limitations on how to understand objects. LiDAR treats any obstacle as something solid, so don’t try to push a cloth valance to clean under your bed or couch, for example. This problem can be solved by removing any fabric “barriers” out of the way before sending your bot to clean it. Floor mirrors are also known to mess with the reflected light beams, causing inaccuracies in mapping. Overall, though, it’s an excellent navigation technology.
What is vSLAM?
vSLAM is less common in modern robovacs, although one notable exception is that all of iRobot’s Roomba robots use it. vSLAM uses visual information from the robovac’s on-board camera to help create a map of the space and understand its position and orientation within it. You will sometimes find vSLAM referred to as “camera-based mapping”.
Like the major brand of robovac Ecovacs explains: “vSLAM gives a vacuum robot the ability to navigate a house with a camera … to capture images of its surroundings and identify specific points, such as corners or edges of furniture. The device then uses these points to triangulate its 3D position and create a map of your home.”
Pros and cons of vSLAM
Since vSLAM uses the robot’s camera, there is no need to have that raised central puck (necessary for LiDAR navigation). This means that the bot usually has a shallow profileand can clean in areas that could be off-limits to higher robovacs.
Unfortunately, this is for the pros in relation to LiDAR vs vSLAM. vSLAM uses a lot of computational power, which makes it significant slower and less effective. It also seems to be less precise – vSLAM based bots can have a habit of embarking on illogical cleaning routes and crashing into things as they go.
vSLAM bots can struggle to find its way around if the room is not well lit. Many come equipped with an LED headlight to try to counter this, but you may also want to turn on your lights before sending your robovac out for cleaning. This could be annoying if you want your robovac to clean while you’re out during the day, in areas that lack natural light. vSLAM-based robovacs may also have difficulty navigating areas that do not have many distinguishable features.
LiDAR vs vSLAM: which is better?
For most people, LiDAR will prove to be the superior system. LiDAR navigation is faster and more reliable, with the bot cleaning logically in a straight line. The room does not need to be well lit to operate effectively.
vSLAM navigation is slower and less efficient. The bot can struggle to find its way around dimly lit areas, or rooms without clear landmarks, and navigation can be convoluted as well. The only benefit of vSLAM over LiDAR is that it does not require an elevated central puck, so the robot can be shallower in profile, and potentially able to reach places that a LiDAR-based bot cannot.
