Excerpted from a new post at our DIY Robocars sister site:
It’s now possible to buy small scanning 2D Lidars for less than $400 these days, which is pretty amazing, since they were as much as $30,000 a few years ago. But how good are they for small autonomous vehicles?
I put two to the test: the RP Lidar A2 (left above) and the Scanse Sweep (right). The RP Lidar A2 is the second lidar from Slamtec, a Chinese company with a good track record. Sweep is the first lidar from Scanse, a US company, and was a Kickstarter project based on the Lidar-Lite 3 1D laser range finder unit that was also a Kickstarter project a few years ago (I was an adviser for that) and is now part of Garmin.
The good news is that both work. But in practice, the difference between them become very stark, with the biggest being the four times higher resolution of the RP Lidar A2 (4,000 points per second, versus Sweep’s 1,000), which makes it actually useful outdoors in a way that Sweep is not. Read on for the details.
First, here are the basic spec comparisons:
Bottom line: RP Lidar A2 is smaller, much higher resolution, and better range indoors (it’s notable that the real-world RP Lidar performance was above the stated specs, while the Scanse performance was below its stated specs). The Scanse desktop visualization software is better, with lots of cool options such as line detection and point grouping, but in practice you won’t use it since you’ll just be reading the data via Python in your own code. Sadly the Scanse code that does those cool things does not appear to be exposed as libraries or APIs that you can use yourself.
In short, I recommend the RP Lidar A2.
I tested them both in small autonomous cars, as shown below (RP Lidar at left)
Both have desktop apps that allow you to visualize the data. Here’s a video of the the two head-to-head scanning the same room (RP Lidar is the window on the right)
You can see difference in resolution pretty clearly in that video: the RP Lidar just has four times as many points, and thus four times higher angular resolution. That means it can not only see smaller objects at a distance, but the objects it does see have four times as many data points, making it much easier to differentiate them from background noise.
As far as using them with our RaspberryPi autonomous car software, it’s a pretty straightforward process of plugging them into the RaspberryPi via the USB port (the RP Lidar should be powered separately, see the notes below) and reading the data with Python. My code for doing this is in my Github repository here. We haven’t decided how best to integrate this data with our computer vision and neural network code, but we’re working on that now — watch this space
Read the rest here
@jesse: All my tests were done outside in direct sunlight. The RP Lidar consistently outperformed its datasheet, the Scanse consistently underperformed.
I looked more closely at their documentation and "Based on laser triangulation principal" in their documentation makes it pretty clear the RP is a Neato vacuum cleaner type laser triangulation based system.
Personally I think TOF is the main way forward for 3D systems in general, but this technology may have OK uses in some sorts of object detection and avoidance.
Thank you for responding.
Actually based on the information it seems more likely to be true TOF rather than angle sensing and looking at your plots it suggests consistent resolution at any range which is characteristic of TOF.
It is curious that they don't bother to mention any of that in their literature.
It is also good to know that you have achieved these comparative results, that is most important information.
I had already asked them this question on their contact section of their web site a couple weeks ago.
I received no reply.
The Neato type angle detection system has progressively deteriorating resolution as you get further and further away, it is intrinsic to the technique.
TOF has constant resolution at any point inside it's range.
If RP is TOF it looks like a great system, and 4 to 5 meters outdoors is certainly suitable for a lot of robotic uses, albeit not automotive interaction ones.
Not sure. The datasheet is here but doesn't seem to answer that. All I know it that blows the Scanse away in practice.
A quick question, from looking at the front of the 2 "Lidars" I would have thought the RPLidar might be using angular sensing data rather than true TOF range finding, but from what seems to be said here, that does not appear to be the case.
I know the Scanse sweep is using TOF because they are based on Lidar Lite 2 or 3.
If possible, could you please clarify actual technology used by RP Lidar? True TOF or Neato Vacuum type angle sense.?
They provide no information on this on their main web site that I could find.