LiDAR Odometry - 5 Minutes with Cyrill
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- เผยแพร่เมื่อ 21 ก.ย. 2024
- LiDAR Odometry explained in 5 minutes using KISS-ICP as an example
Code: github.com/PRB...
Series: 5 Minutes with Cyrill
Cyrill Stachniss, 2022
Credits:
Video by Cyrill Stachniss
Thanks to the KISS-ICP developers Ignacio Vizzo, Tiziano Guadagnino, Benedikt Mersch, Louis Wiesmann, and Jens Behley
Thanks to Igor Bogoslavskyi and Olga Vysotska
Intro music by The Brothers Records
Really good video. I find these 5 minutes are a great way to refresh material.
It is extremely cool that the KISS-ICP developers decided to release their code, especially in such a polished manner. Too much research code is left to rot on university hard drives :(
Thanks
Thank you so much for sharing exceptional content and research. The effort is really impressive and have remarkable impact for whole robotics domain and autonomous vehicles. I love this channel and especially the high quality of the content. Great also that the channel is shared among the other team members. Good luck. Have a nice day!
Thanks!
At startup, it gave an error. I updated the firewood and it helped me)
Thank you so much for your talk, These series are great.
Auf den Punkt in 5 Minuten!
Cannot wait to try KISS-ICP with point cloud from livox HAP lidar, which has FOV 120
Thank you for the explanation.
It really works, thank you.
Great , happy to hear that!
WOW thank you so much Sir.
Очень интересно)
Really nice video. Right now I am researching about the lidar SLAM algorithms. Especially for the tunnel environment where it is dark and not manny features are present. I am wondering about the performance of the KISS-ICP in such environment. Also in the paper there is comparison of KISS-ICP with other state-of-the-art algorithms. I am wondering why algorithms such as Fast-Lio2, LeGO-LOAM, SC-LeGO-LOAM, LIO-SAM were not included in the comparison? Thank you
I'm just making assumptions here. KISS-ICP is a LiDAR Odometry method, which only takes LiDAR's point cloud as inputs, maybe that's why Fast-LIO and LIO-SAM are not counted as comparisons since they are LiDAR-Inertial methods. SC-LeGO-LOAM contains a global point cloud descriptor to perform loop closure and backend optimization, and KISS-ICP mainly focuses on frame-to-frame alignment.
I see, thank you for your input
Hi Prof Stachniss, Thank you for sharing the novel KISS-ICP! I wonder if KISS-ICP works fine as well for 2D laser scanner.
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Yes it does, out of the box, although not designed for it 🙃
This is great! I figure that, at 40Hz processing frequency, a moving environment won't affect the algorithm too much... But have you been conducting tests in highly dynamic environments? The paper mentions a few standard data sets you tested on, but I'm not familiar with these. Would be great to get a quick idea how dynamic environments can get for this to still work.
It works quite well. Simply run it on your dynamics ans see how it works for you - running it ist faster than me typing in the dataset names on my smartphone 😉
Will this work for a planar lidar?
Yes it does
Hey cyrill any lidar odometry which we can use for 2d lidar
Kiss-icp should also work in 2d