NeroBurner
a548766d14
Update the usage of Google Flags (gflags) library the same way Glog updated it [1]. This pushes the minimum required gflags version to v2.2.0. Remove the ceres specific define of CERES_GFLAGS_NAMESPACE and directly use GFLAGS_NAMESPACE defined in gflags/gflags_declare.h [2]. In CeresConfig.cmake the hard coded paths for gflags are ommited. Instead we rely on the gflagsConfig file to get closer to a relocatable CeresConfig.cmake. Furthermore use the find_dependency() [4] cmake function specifically created for cmake-config files. This change builds upon the explicit PUBLIC/PRIVATE link change [3]. [1] https://github.com/google/glog/pull/199 [2] https://github.com/gflags/gflags/blob/d9b184bd0026b16bb4c2fded75d56fb2cce50d66/src/gflags_declare.h.in#L43 [3] https://ceres-solver-review.googlesource.com/c/ceres-solver/+/16220 [4] https://cmake.org/cmake/help/latest/module/CMakeFindDependencyMacro.html Change-Id: I9861a2699f2702bf1a5e99d07863a7e6639b7c39
Pose Graph 2D
The Simultaneous Localization and Mapping (SLAM) problem consists of building a map of an unknown environment while simultaneously localizing against this map. The main difficulty of this problem stems from not having any additional external aiding information such as GPS. SLAM has been considered one of the fundamental challenges of robotics. A pose graph optimization problem is one example of a SLAM problem.
This package defines the necessary Ceres cost functions needed to model the 2-dimensional pose graph optimization problem as well as a binary to build and solve the problem. The cost functions are shown for instruction purposes and can be speed up by using analytical derivatives which take longer to implement.
Running
This package includes an executable pose_graph_2d that will read a problem
definition file. This executable can work with any 2D problem definition that
uses the g2o format. It would be relatively straightforward to implement a new
reader for a different format such as TORO or others. pose_graph_2d will print
the Ceres solver full summary and then output to disk the original and optimized
poses (poses_original.txt and poses_optimized.txt, respectively) of the
robot in the following format:
pose_id x y yaw_radians
pose_id x y yaw_radians
pose_id x y yaw_radians
...
where pose_id is the corresponding integer ID from the file definition. Note,
the file will be sorted in ascending order for the pose_id.
The executable pose_graph_2d has one flag --input which is the path to the
problem definition. To run the executable,
/path/to/bin/pose_graph_2d --input /path/to/dataset/dataset.g2o
A python script is provided to visualize the resulting output files.
/path/to/repo/examples/slam/pose_graph_2d/plot_results.py --optimized_poses ./poses_optimized.txt --initial_poses ./poses_original.txt