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[RA-L 2024] In Defense of LiDAR-Only Odometry Using an Effective Continuous-Time Trajectory

License: MIT License

CMake 0.44% C++ 26.41% C 72.52% GLSL 0.47% Shell 0.16%

continuous-time lidar-slam robotics lidar-only

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zjuiv liuxinren456852 lurvelly dodeakim luohongk juexiaofficial tops666 yunhui-li weixiaopassking

traj-lo's Issues

Loop Closure And Map Saving

You have done a really amazing job regarding map quality!

But I would like to know if there is a loop closure module as from my tests, it seems that there is no loop closure.

For the map, is there a way to save a generated map in pcd? Also, can i extract the path to be used with evo evaluation tool?

Be aware of License Terms 😉

Hello, thanks for opening the source code for the benefit of the community.

I'm very happy to see many patterns we've developed with much love and effort for KISS-ICP. It definitely makes your implementation stand against the usual ones we see in LiDAR odometry.

Although I would recommend being a bit more conservative when it comes to copying code from other projects, even when you don't pay for it, there are licensing terms:
https://github.com/PRBonn/kiss-icp/blob/11c7d97d156a7ff72fefdacc3105db4a99805e0e/LICENSE#L13-L14

Just to name a few

Traj-LO/include/trajlo/core/map_manager.h

Lines 42 to 59 in f04d15a

 struct VoxelBlock { 

 // buffer of points with a max limit of n_points 

 std::vector<Eigen::Vector3d> points; 

 int num_points_; 

 inline void AddPoint(const Eigen::Vector3d &point) { 

 if (points.size() < static_cast<size_t>(num_points_)) 

 points.push_back(point); 

 } 

 }; 

 struct VoxelHash { 

 size_t operator()(const Voxel &voxel) const { 

 const uint32_t *vec = reinterpret_cast<const uint32_t *>(voxel.data()); 

 return ((1 << 20) - 1) & 

 (vec[0] * 73856093 ^ vec[1] * 19349663 ^ vec[2] * 83492791); 

 } 

 };

Looks WAY too similar too
https://github.com/PRBonn/kiss-icp/blob/11c7d97d156a7ff72fefdacc3105db4a99805e0e/cpp/kiss_icp/core/VoxelHashMap.hpp#L36-L51

I don't mind at ALL that you reuse some code. Just be mindful of not claiming it as yours, as you claim in your license.

Support for MID-40？

Thanks for releasing the code! I'm wondering if Traj-LO supports Livox MID-40? We tried to run Traj-LO with our bags. However, we encountered with Segmentation fault.

I printed the time taken for each iteration of the while (true) loop on line 67 in the odometry.cpp file. Below is a part of the output:
dometry computation took 70.6064 milliseconds.
odometry computation took 108.871 milliseconds.
odometry computation took 87.9254 milliseconds.
odometry computation took 99.0804 milliseconds.
odometry computation took 85.6526 milliseconds.
odometry computation took 84.4505 milliseconds.
odometry computation took 111.856 milliseconds.
odometry computation took 106.236 milliseconds.
odometry computation took 79.5079 milliseconds.
odometry computation took 70.2243 milliseconds.
odometry computation took 101.104 milliseconds.
odometry computation took 102.121 milliseconds.
odometry computation took 80.6436 milliseconds.
odometry computation took 71.5117 milliseconds.
odometry computation took 104.166 milliseconds.
odometry computation took 75.5676 milliseconds.
odometry computation took 126.864 milliseconds.
odometry computation took 119.489 milliseconds.
odometry computation took 88.3249 milliseconds.
odometry computation took 69.8241 milliseconds.

Is there any schedule for code release

Nice work! Any idea when the code will be released ? Thanks

Inquiry about running NTU-VIRAL dataset with config_ntu.yaml

Thank you for your excellent open-source lidar odometry.

I evaluated the TRAJ-LO on the NTU-VIRAL dataset with the ./trajlo ../data/config_ntu.yaml, but could not get consistent ATE results with the paper published on RA-L. The ATE is getting from the official evaluation python script from NTU-VIRAL dataset . Could you give me some advice about how to get a consistent ATE with the results illustrated in your paper?
Moreover, the ./trajlo ../data/config_ntu.yaml seems useful for single lidar odometry, but does not work for the multi-lidar odometry. How can I run TRAJ-LO with multiple lidar?

Looking forward to your reply.

kevin2431 / traj-lo Goto Github PK

traj-lo's People

Contributors

Stargazers

Watchers

Forkers

traj-lo's Issues

Loop Closure And Map Saving

Be aware of License Terms 😉

Support for MID-40？

Can Traj-LO run in real-time?

Is there any schedule for code release

Inquiry about running NTU-VIRAL dataset with config_ntu.yaml

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	struct VoxelBlock {
	// buffer of points with a max limit of n_points
	std::vector<Eigen::Vector3d> points;
	int num_points_;

	inline void AddPoint(const Eigen::Vector3d &point) {
	if (points.size() < static_cast<size_t>(num_points_))
	points.push_back(point);
	}
	};

	struct VoxelHash {
	size_t operator()(const Voxel &voxel) const {
	const uint32_t vec = reinterpret_cast<const uint32_t >(voxel.data());
	return ((1 << 20) - 1) &
	(vec[0] * 73856093 ^ vec[1] * 19349663 ^ vec[2] * 83492791);
	}
	};