Lidar mapping techniques using multiple sensors
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Re: Lidar mapping techniques using multiple sensors
#2The SLAM approach will work well with a validated point cloud and a new set of points for fixed objects. However if you are mapping movable or alterable objects such as vegetation I am unsure if the algorithm will still yield highly accurate results.
Another thing to consider is that if you are basing future measurements on past measurements, you need to be accurate to less than 1cm in the absolute X,Y,Z position of those points, and account for drift across your collection area. Small errors will add up to large differences in the survey set.
Re: Lidar mapping techniques using multiple sensors
#3The SLAM approach will work well with a validated point cloud and a new set of points for fixed objects. However if you are mapping movable or alterable objects such as vegetation I am unsure if the algorithm will still yield highly accurate results. Another thing to consider is that if you are basing future measurements on past measurements, you need to be accurate to less than 1cm in the absolute X,Y,Z position of…
> However if you are mapping movable or alterable objects such as vegetation I am unsure if the algorithm will still yield highly accurate results.
If most objects are fixed, won't the best solution still be the correct one?
Re: Lidar mapping techniques using multiple sensors
#4The SLAM approach will work well with a validated point cloud and a new set of points for fixed objects. However if you are mapping movable or alterable objects such as vegetation I am unsure if the algorithm will still yield highly accurate results. Another thing to consider is that if you are basing future measurements on past measurements, you need to be accurate to less than 1cm in the absolute X,Y,Z position of…
> However if you are mapping movable or alterable objects such as vegetation I am unsure if the algorithm will still yield highly accurate results. If most objects are fixed, won't the best solution still be the correct one?
Good question; I am not sure. Imagine if someone were using the SLAM approach to map farm corn fields, in order to determine plant growth rates over the growing season. In that scenario I would think that the majority of the points would be returned from surfaces which were not present in the original point cloud. Of course you could set up ground control stations, surveyed using traditional techniques, and align the new data to them but then you are back to the original point cloud alignment process.
Re: Lidar mapping techniques using multiple sensors
#5Earlier quoted context omitted.
> However if you are mapping movable or alterable objects such as vegetation I am unsure if the algorithm will still yield highly accurate results. If most objects are fixed, won't the best solution still be the correct one?
Good question; I am not sure. Imagine if someone were using the SLAM approach to map farm corn fields, in order to determine plant growth rates over the growing season. In that scenario I would think that the majority of the points would be returned from surfaces which were not present in the original point cloud. Of course you could set up ground control stations, surveyed using traditional techniques, and align the…
If you're mapping corn fields, GPS + IMU will yield very good results. I wouldn't use any kind of SLAM in a farm field, it will probably worsen the position given by the GPS + IMU!!
Re: Lidar mapping techniques using multiple sensors
#6The SLAM approach will work well with a validated point cloud and a new set of points for fixed objects. However if you are mapping movable or alterable objects such as vegetation I am unsure if the algorithm will still yield highly accurate results. Another thing to consider is that if you are basing future measurements on past measurements, you need to be accurate to less than 1cm in the absolute X,Y,Z position of…
I (and OP for that matter) do mapping with sensors with accuracies that are around 2 cm. I don't know where you got that 1 cm requirement from. ICP/SLAM drift will happen even with a perfect sensor. It really depends on the scale of what you are trying to measure.
There are ways to work with dynamic environments in lidar SLAM: https://ieeexplore.ieee.org/abstract/document/6907397
Re: Lidar mapping techniques using multiple sensors
#7The SLAM approach will work well with a validated point cloud and a new set of points for fixed objects. However if you are mapping movable or alterable objects such as vegetation I am unsure if the algorithm will still yield highly accurate results. Another thing to consider is that if you are basing future measurements on past measurements, you need to be accurate to less than 1cm in the absolute X,Y,Z position of…
I funded a paper mapping vegetation in a forest, if you're curious: https://www.philsalesses.com/s/a582379.pdf
IIRC, the lidar still lined up mostly because tree stems tend to not move, however, the larger problem was the error rate of the lidar sensor we were using. Readings further than 10m and the Hokuyo we were using tended to underestimate distances, so each scan of the forest looked a little but like the floor was curving over like that scene from Inception. Although maybe only 20 degrees. Still enough to be annoying.
Re: Lidar mapping techniques using multiple sensors
#8The SLAM approach will work well with a validated point cloud and a new set of points for fixed objects. However if you are mapping movable or alterable objects such as vegetation I am unsure if the algorithm will still yield highly accurate results. Another thing to consider is that if you are basing future measurements on past measurements, you need to be accurate to less than 1cm in the absolute X,Y,Z position of…
At the NASA autonomy incubator we had a search and rescue under the canopy project[1] that successfully used SLAM along with other methods in such an environment.
Re: Lidar mapping techniques using multiple sensors
#9The SLAM approach will work well with a validated point cloud and a new set of points for fixed objects. However if you are mapping movable or alterable objects such as vegetation I am unsure if the algorithm will still yield highly accurate results. Another thing to consider is that if you are basing future measurements on past measurements, you need to be accurate to less than 1cm in the absolute X,Y,Z position of…
I funded a paper mapping vegetation in a forest, if you're curious: https://www.philsalesses.com/s/a582379.pdf IIRC, the lidar still lined up mostly because tree stems tend to not move, however, the larger problem was the error rate of the lidar sensor we were using. Readings further than 10m and the Hokuyo we were using tended to underestimate distances, so each scan of the forest looked a little but like the floor…
Hey, I'm familiar with your work! I'm currently submitting similar work using a Husky and a Velodyne HDL-32. I don't have the problem you mention with my sensor. See: https://www.youtube.com/watch?v=V-Q-XWSWT-I&index=2&list=UUo...
Re: Lidar mapping techniques using multiple sensors
#10The SLAM approach will work well with a validated point cloud and a new set of points for fixed objects. However if you are mapping movable or alterable objects such as vegetation I am unsure if the algorithm will still yield highly accurate results. Another thing to consider is that if you are basing future measurements on past measurements, you need to be accurate to less than 1cm in the absolute X,Y,Z position of…
At the NASA autonomy incubator we had a search and rescue under the canopy project[1] that successfully used SLAM along with other methods in such an environment. [1]: https://www.youtube.com/watch?v=2hRNx_0SWGw
Thanks for the linked video, that sounds like an interesting project. Can the system in the project identify vegetation stems from above the canopy? Are the vegetation stems the only points of reference for the drone swarms other than their individual search area boundaries?