Comments (12)
Thanks for your interest. But I didn't meet this problem. Would you please tell me the actual cpu type?
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I use a Nvidia Jetson AGX Xavier which has an ARM-based processor.
Are you cross-compiling the code or are you directly compiling the code on the target machine (i.e. the dji manifold computer)?
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from fast_lio.
I use a Nvidia Jetson AGX Xavier which has an ARM-based processor.
Are you cross-compiling the code or are you directly compiling the code on the target machine (i.e. the dji manifold computer)?
We are currently working on the implementation on the ARM based platform. The long building time truely exists, several minutes (around 3 minutes) should be taken in my tests.
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你的编译成功了吗?我的manifold2-c已经第二次出现扩展板损坏,原因可能是电路设计的问题,维修了两次。所以,我也在考虑是否更换成你的这个mini计算机,希望能得到你的帮助! 谢谢🙏!
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------------------ Original ------------------ From: mbcel @.> Date: Wed,May 5,2021 3:35 AM To: hku-mars/FAST_LIO @.> Cc: Subscribed @.***> Subject: Re: [hku-mars/FAST_LIO] Long build times for loam_mapping/loam_feature_extract (#14) I use a Nvidia Jetson AGX Xavier which has an ARM-based processor. Are you cross-compiling the code or are you directly compiling the code on the target machine (i.e. the dji manifold computer)? — You are receiving this because you are subscribed to this thread. Reply to this email directly, view it on GitHub, or unsubscribe.
You may consider trying intel NUC, its hardware is more stable than manifold 2c and sells cheaper. Only problem is the weight may be a little bigger than manifold 2c.
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Hm okay. What puzzels me is that this long build time occures on every code change in the laserMapping.cpp
file. It seems like the linking process here takes over a minute and needs to be done on ANY change.
Do you experience the same on your ARM platform or do you have such long build times only for the first initial build?
If yes, how do you cope with this? Are you cross-compiling on a different machine or something like that? To wait more than a minute after each code change makes it impossible for me to code properly.
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what about raspbery pi 4 arm arhitecture?
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what about raspbery pi 4 arm arhitecture?
fast-lio can work on raspberry but remember to close rviz since rviz will consume too much computing resources.
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Related Issues (20)
- Gmapping navigation HOT 3
- The fineness of point cloud display in rviz HOT 1
- 里程计输出频率问题? HOT 1
- FAST_LIO uses only one core of the CPU HOT 1
- Is IMU optional? HOT 3
- 话题/Laser_map为空 HOT 3
- Some Clarification in Code HOT 2
- Is livox_ros_driver2 required at all? HOT 3
- process has died exit code 11 HOT 4
- How to get a trajectory format that can be used for evo tool ? HOT 1
- Intitialize in known geographic coordinates HOT 1
- fastlio+livox HOT 2
- make livox driver dependency optional HOT 1
- Memory leak HOT 15
- Process dying exit code 127 HOT 1
- Segmentation fault (due to placeholders warning in boost? HOT 2
- Topic /tf has no timestamp in ROS2 branch HOT 1
- error for rclcpp::AnyServiceCallback
- Inconsistent Z position estimate in outdoor unstructured environments HOT 1
- How does lidar noise work? HOT 1
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