Fangcheng Zhu

https://zfc-zfc.github.io/zhufangcheng.github.io/

HITsz & HKU Shenzhen, China [email protected]

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                                            Fangcheng Zhu

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标定进度条跑太快，结果不太准确

> 首先，没有明显差别不代表没有差别，只是肉眼看不出来：你可以在有真值的场景采集数据做测试，比如motion capture做真值；其次，imu的propagation只是提供一个初值，建图最主要还是靠点云配准，只要初值不差的离谱，迭代次数足够，初值好一点次一点都可能收敛到接近的程度。你要验证区别，最简单的方式就是你让雷达和imu的外参大一些，比如旋转180°，一个采用单位阵作为旋转外参，一个采用标定结果，区别就很大了。

wating for code

> Great work. It has been 5 months this repo is not updated. Any update about the release of code. Thank you Sorry for the delay in the open-source process...

Livox Horizon反复多次标定，内置IMU的线加速度比激光雷达的线加速度差别非常大，几乎无法重合

> 汇报一下：我又重新看了下大神的视频，我发现我的移动方式有问题，不是视频中的这个样子，因此我又重新按照视频里的移动轨迹，重新做了5次校准。结果好了不少，但是还是不够理想： > > ![image](https://private-user-images.githubusercontent.com/3270742/369258087-ce615fda-6cbb-4f41-a445-9059acb71ac7.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.9kREWd3ihFaQvVVnq8zo9kWfb62XaYQpWEBeJnbeuko) > > ![image](https://private-user-images.githubusercontent.com/3270742/369258151-9699b2a2-99c7-4105-8049-7bb2ada75443.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.MYoMCd7mwpw5EHBZUGHCGP6CqbQCNv32C1V3ag2Q_6Y) > > ![image](https://private-user-images.githubusercontent.com/3270742/369259110-960155a6-9d9e-4272-af0f-7cfd07d4d1e9.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.GQR2OXT2jiweNjzJAYVwEgegKUUh__xs7B4Kd1MQjWw) > > ![image](https://private-user-images.githubusercontent.com/3270742/369259388-e3889c96-bd54-40c0-91fd-2f360fcd407a.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.81h0eMNuZaJXytPcfBQU8N08exe07kjhVJGbve-AKX8) > > ![image](https://private-user-images.githubusercontent.com/3270742/369259741-d7d92bf3-0048-47a9-89e5-5c3aefe96ab1.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.6TZq7Xn3TKKPkLXRi-ojO_qEZlNmf1jVB8cKrOjpGiE) > > ![image](https://private-user-images.githubusercontent.com/3270742/369259974-81239e96-09ec-4df6-9ee4-d865764bf5c8.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.MV42y-iBr3d1RZHFEbWCq15K0WzgqImbZZ8bHa20aMg) 加速度的质量很依赖于LO的精度，而LO的精度比较依赖场景，可以尽量选一个平面特征多的场景，比如地下车库，建筑物内部。可以看看你的yaml参数表吗？

Livox Horizon反复多次标定，内置IMU的线加速度比激光雷达的线加速度差别非常大，几乎无法重合

> > > 汇报一下：我又重新看了下大神的视频，我发现我的移动方式有问题，不是视频中的这个样子，因此我又重新按照视频里的移动轨迹，重新做了5次校准。结果好了不少，但是还是不够理想： > > > ![image](https://private-user-images.githubusercontent.com/3270742/369258087-ce615fda-6cbb-4f41-a445-9059acb71ac7.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MzI1Mzc1OTksIm5iZiI6MTczMjUzNzI5OSwicGF0aCI6Ii8zMjcwNzQyLzM2OTI1ODA4Ny1jZTYxNWZkYS02Y2JiLTRmNDEtYTQ0NS05MDU5YWNiNzFhYzcucG5nP1gtQW16LUFsZ29yaXRobT1BV1M0LUhNQUMtU0hBMjU2JlgtQW16LUNyZWRlbnRpYWw9QUtJQVZDT0RZTFNBNTNQUUs0WkElMkYyMDI0MTEyNSUyRnVzLWVhc3QtMSUyRnMzJTJGYXdzNF9yZXF1ZXN0JlgtQW16LURhdGU9MjAyNDExMjVUMTIyMTM5WiZYLUFtei1FeHBpcmVzPTMwMCZYLUFtei1TaWduYXR1cmU9M2FmNmU4NTI4Yzk3OGJiZjkxYTlkOTk4YjllYTA5ODAzOGRlYjJjMzgxYmQ0OGI2ZjE0OGI2NDMzMzQwMDcxOSZYLUFtei1TaWduZWRIZWFkZXJzPWhvc3QifQ.9kREWd3ihFaQvVVnq8zo9kWfb62XaYQpWEBeJnbeuko) > > > ![image](https://private-user-images.githubusercontent.com/3270742/369258151-9699b2a2-99c7-4105-8049-7bb2ada75443.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.MYoMCd7mwpw5EHBZUGHCGP6CqbQCNv32C1V3ag2Q_6Y) > > > ![image](https://private-user-images.githubusercontent.com/3270742/369259110-960155a6-9d9e-4272-af0f-7cfd07d4d1e9.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.GQR2OXT2jiweNjzJAYVwEgegKUUh__xs7B4Kd1MQjWw) > > > ![image](https://private-user-images.githubusercontent.com/3270742/369259388-e3889c96-bd54-40c0-91fd-2f360fcd407a.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.81h0eMNuZaJXytPcfBQU8N08exe07kjhVJGbve-AKX8) > > > ![image](https://private-user-images.githubusercontent.com/3270742/369259741-d7d92bf3-0048-47a9-89e5-5c3aefe96ab1.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.6TZq7Xn3TKKPkLXRi-ojO_qEZlNmf1jVB8cKrOjpGiE) > > > ![image](https://private-user-images.githubusercontent.com/3270742/369259974-81239e96-09ec-4df6-9ee4-d865764bf5c8.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.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.MV42y-iBr3d1RZHFEbWCq15K0WzgqImbZZ8bHa20aMg) > >...

Using Docker. VLP16 and PX4 IMU. Initialization starts to fill when LiDAR+IMU are static and leads to Strange behaviour.

> @zfc-zfc Hi! Thank you so much for the great work. I hope you can help me. > > I'm using a VLP16 LiDAR and a PX4 IMU and I've...

Cloning swarm-odometry

> Facing problem while cloning `swarm-odometry` package > > ``` > mubashir@mubashir:~$ git clone https://gitlab.djicorp.com/swarm-odometry/swarm-odometry.git > Cloning into 'swarm-odometry'... > fatal: unable to access 'https://gitlab.djicorp.com/swarm-odometry/swarm-odometry.git/': Could not resolve host: gitlab.djicorp.com...

Update of Swarm-LIO2 to Swarm-LIVO2

> I am very excited about the release of `Swarm-LIO2`. I have a question: As LiDAR odometry techniques evolve over time, will `Swarm-LIO2` be compatible with `LIVO2` or other SLAM...

标定结果与环境位置距离有关系吗

> 您好，非常感谢您的工作，我对您的工作很感兴趣，但有几点问题想向您请教一下。 1.在livox使用内置imu标定的过程中这个场景中环境地图的距离与标定结果之间的关系是什么样的？对结果的影响如何？ 2.标定过程不涉及标定板的话如何选择标定的场景对标定结果的影响又是什么样的呢？期待您的回复有关系的。尽量选择约束充分，平面特征多的场景会获得更高精度的LO，从而获得更高的标定精度。

关于点云数据的问题

> 请问这个代码支持无组织的点云数据吗？感谢！只要点云里包含每个点的时间戳信息，有序无序都无所谓的

禾赛激光雷达16线雷达与阿路比LPMS-IG1 RS485IMU标定问题

> ![微信图片_20241225113620](https://private-user-images.githubusercontent.com/178983559/398519285-6142778c-40f8-4753-a07d-0fad339f866c.png?jwt=eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJnaXRodWIuY29tIiwiYXVkIjoicmF3LmdpdGh1YnVzZXJjb250ZW50LmNvbSIsImtleSI6ImtleTUiLCJleHAiOjE3MzU4MDAzNDEsIm5iZiI6MTczNTgwMDA0MSwicGF0aCI6Ii8xNzg5ODM1NTkvMzk4NTE5Mjg1LTYxNDI3NzhjLTQwZjgtNDc1My1hMDdkLTBmYWQzMzlmODY2Yy5wbmc_WC1BbXotQWxnb3JpdGhtPUFXUzQtSE1BQy1TSEEyNTYmWC1BbXotQ3JlZGVudGlhbD1BS0lBVkNPRFlMU0E1M1BRSzRaQSUyRjIwMjUwMTAyJTJGdXMtZWFzdC0xJTJGczMlMkZhd3M0X3JlcXVlc3QmWC1BbXotRGF0ZT0yMDI1MDEwMlQwNjQwNDFaJlgtQW16LUV4cGlyZXM9MzAwJlgtQW16LVNpZ25hdHVyZT1lMDE0ZTk2NDQzZTJiNjZjZDJmNWE1NTYxMjA2NmYzMTlmNGY2MTQ4Yjk3OTg2M2FlODFjMzc2NDExMjYwOGQwJlgtQW16LVNpZ25lZEhlYWRlcnM9aG9zdCJ9.xVXlhjzKeV-ZVCJXsFAmYDoXhunE_IaSaWwAK0z631c) 请问16线的与32线相比要改什么参数啊，imu不一样要改哪些地方。上面只改了imu的话题运行出来得出的问题。理论上只需要把线数 scan_line 改掉就好。可以把参数表和rosbag上传网盘分享一下吗？