Comments (3)
我刚才测了一下感觉没什么太大问题,截图结果如下。另外我一会儿单独为MARS-LVIG dataset创建一个配置文件然后push上去吧,方便大家复现,之后你可以再测试下哈。但最好你能用gdb检查下到底问题出在哪行#53,我比较担心是你的环境配置问题。
from fast-livo.
非常感谢您的回答,很有帮助,我用gdb调试后打印信息如下
[ VIO ]: Add 0 3D points.
[ VIO ]: time: addFromSparseMap: 0.000011 addSparseMap: 0.000055 ComputeJ: 0.000004 addObservation: 0.000002 total time: 0.000072 ave_total: 0.000072.
[ LIO ]: Raw feature num: 11893 downsamp num 10911 Map num: 10964.
[ LIO ]: Using multi-processor, used core number: 4.
[New Thread 0x7fff923f8700 (LWP 18464)]
[New Thread 0x7fff91bf7700 (LWP 18465)]
[New Thread 0x7fff913f6700 (LWP 18466)]
[ LIO ]: time: fov_check: 0.000000 fov_check and readd: 0.002638 match: 0.000000 solve: 0.000000 ICP: 0.001149 map incre: 0.031386 total: 0.035173 icp: 0.000780 construct H: 0.000000.
[ INFO ]: get point cloud at time: 1658137064.324880.
[ VIO ]: Raw feature num: 11893.
[ VIO ]: Add 1761 3D points.
[ VIO ]: time: addFromSparseMap: 0.000001 addSparseMap: 0.006574 ComputeJ: 0.000000 addObservation: 0.000000 total time: 0.006576 ave_total: 0.006576.
[ INFO ]: get img at time: 1658137064.440385.
[ LIO ]: Raw feature num: 11898 downsamp num 10905 Map num: 17091.
[ LIO ]: Using multi-processor, used core number: 4.
[ LIO ]: time: fov_check: 0.000000 fov_check and readd: 0.002378 match: 0.000000 solve: 0.000000 ICP: 0.002737 map incre: 0.020595 total: 0.030441 icp: 0.001689 construct H: 0.000000.
[ INFO ]: get img at time: 1658137064.540787.
[ INFO ]: get point cloud at time: 1658137064.424726.
[ VIO ]: Raw feature num: 11898.
Thread 1 "fastlivo_mappin" received signal SIGSEGV, Segmentation fault.
0x00007ffff32a6088 in lidar_selection::LidarSelector::addFromSparseMap (
this=this@entry=0x55555c87d3c0, img=..., pg=...)
at /home/maxi/FASTLIVO_ws/src/FAST-LIVO/src/lidar_selection.cpp:376
376 float it[height*width] = {0.0};
(gdb)
然后参考您给的 #53 ,我把lidar_selection.cpp的376行的float it[height * width] = {0.0};改为了std::vector it(height*width, 0); 再重新编译后运行,便可以基于MARS-LVIG dataset跑起来了。
但是运行不了多长时间(不到一分钟),终端就会报红挂掉,从gnome-system-monitor里面可以看到,FAST-LIVO运行起来后,内存占用一直在累积上升,到达百分之百之后程序终端就会卡住报红挂掉。我是普通笔记本上跑的,内存是16G。似乎和这个 #105 类似是么。
但在跑FAST-LIVO-Datasets里的hku1.bag是可以运行相对长点的时间而且跑完的。
from fast-livo.
相同的地图分辨率,大尺度场景内存涨的会越快,因为每帧的raw points会有特别多的点被用来更新地图。可以试着调低filter_size_map
,关掉rviz,或增加swap空间。另外我已经上传了MARS-LVIG的参数和launch文件,并为了适配做了一些的代码修改。如果想要速度更快,内存占用更低的版本,可以follow下FAST-LIVO2。
from fast-livo.
Related Issues (20)
- omp_set_num_threads(MP_PROC_NUM); 一旦打开,LIO部分,计算点到面会使用多个线程,这是合理的,但为什么在IEKF求解位姿的过程也是多个线程各自进行求解呢? HOT 17
- Crops and Overlays an upper corner - Fast-Livo with VLP16 and Zed2 HOT 1
- No such file or directory #include <fast_livo/States.h> HOT 2
- corrupted size vs. prev_size [laserMapping-2] process has died HOT 3
- How can I save it as pcd? when I finished the process of mapping? HOT 1
- error when running your dataset HOT 2
- Mid360适配 HOT 6
- Problems running your own lab dataset mid360 and ouster128 HOT 8
- Mid70不接外置IMU配置文件怎么设置?
- 禾赛雷达适配问题 HOT 5
- 禾赛32线雷达+海康相机 运行问题 HOT 1
- robosense Helios32线激光雷达适配问题 HOT 4
- 内存泄漏导致运行时间不能太长 HOT 2
- How to run our own data (How to generate the .bag data like the sample data)? HOT 1
- 跑kitti数据集时遇到的 HOT 2
- fast-livo运行自己的数据集时会产生漂移现象 HOT 1
- 位姿估计只使用了可见光相机,如果使用红外相机做位姿估计的话,需要多考虑什么问题吗? HOT 2
- 关于单开LiDAR模式不如FASTLIO2的浅谈 HOT 1
- LiDAR Camera no common FOV HOT 1
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