- [ X] Keep your PR rebased to master.
- [ X] Keep your PR under 200 lines of code and address a single concern.
- [ X] Add unit test(s) and documentation (these do not count toward your 200 lines).
- [ X] Adhere to the [Google C++ Style Guide](https://google.github.io/styleguide/cppguide.html).
- [ X] Run `clang-format -style=Google` on your code (this alone is not enough to ensure you've followed the style guide).
- [ X] Run `ninja test` or `catkin_make_isolated --install --use-ninja --pkg cartographer --make-args test` as appropriate.
- [ X] Keep your PR rebased to master.
- [ X] Keep your PR under 200 lines of code and address a single concern.
- [ X] Add unit test(s) and documentation (these do not count toward your 200 lines).
- [ X] Adhere to the [Google C++ Style Guide](https://google.github.io/styleguide/cppguide.html).
- [ X] Run `clang-format -style=Google` on your code (this alone is not enough to ensure you've followed the style guide).
- [ X] Run `ninja test` or `catkin_make_isolated --install --use-ninja --pkg cartographer --make-args test` as appropriate.
- Pin versions of Ceres and protobuf (Fixes#341).
- Require Lua >= 5.2 (Fixes#629).
- No longer run ceres tests in CI. We implicitly test Ceres through Cartographer's tests and this saves ~4 minutes on CI.
This adds information about which nodes are contained in which
deserialized submaps. This is necessary for the rotational scan
matcher.
Also skips frozen trajectories when tying together nodes of a
trajectory with IMU data which is unavailable in this case.
- introduce InsertIntoSubmap for 2D
- clarify some variable names in 3D
- move rotational_scan_matcher_histogram calculation
to InsertIntoSubmap for 3D
- refactor last version of range data before insertion into
range_data_in_local (filtered_range_data_in_local for 3D)
This changes the origin of accumulated range data from the
zero vector (which could be far off) to the origin of the
first range data in the accumulation.
Adds a type TimedPointCloud that holds 4-dimensional vectors where measurement time of individual points are stored in the fourth entry.
Uses TimedRangeData to pass TimedPointCloud of incoming measurements to LocalTrajectoryBuilder.
Fixes#573.
This speeds up the asset writer significantly:
For the 3D sample bag:
~~~
/usr/bin/time roslaunch cartographer_ros assets_writer_backpack_3d.launch \
bag_filenames:=${HOME}/Downloads/b3-2016-04-05-14-14-00.bag \
pose_graph_filename:=${HOME}/Downloads/b3-2016-04-05-14-14-00.bag.pbstream
master:
2100.96user 26.79system 35:43.60elapsed 99%CPU (0avgtext+0avgdata 3657028maxresident)k
17682632inputs+32080outputs (0major+20021051minor)pagefaults 0swaps
this CL:
1937.46user 11.77system 32:22.49elapsed 100%CPU (0avgtext+0avgdata 3659412maxresident)k
1352inputs+32088outputs (0major+7042032minor)pagefaults 0swaps
~~~
So ~10%. For pipelines that do less this can be even 30% or more.
- Refactor ProbabilityGridPointsProcessor for code reuse.
- Adds Image::width and height.
- Adds GetFilename for FileWriter.
Related to googlecartographer/cartographer_ros#475.