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distributedmapping's Introduction

DistributedMapping

Requirements

pip install evo --upgrade --no-binary evo

Compilation

mkdir build
cd build
cmake ..
make -j4
./kitti(or ./sphere)
sudo make install

.g2o -> .txt(kitti format)

After compilation, execute

g2oToKitti -n [RobotNumber] -is [inputFilenameSuffix(like _optimized)] -os [outputFilenameSuffix(like _optimized)]
evo_traj kitti [outputFilename(like 0.txt)] -p --plot_mode=xz

For example, if there are files named 0.g2o, 1.g2o,0_optimized.g2o,1_optimized.g2o , you can execute

g2oToKitti -n 2 
g2oToKitti -n 2 -is _optimized -os _optimized

Then you will get 0.txt,1.txt,0_optimized.txt,1_optimized.txtand execute

evo_traj kitti [yourFiles] -p --plot_mode=xz

Data/1/

x.g2o :initial poses
x_optimized.g2o :optimized poses
x_optimizedTUM.txt :optimized posed(TUM format)
initial.g2o	:total initial poses
fullGraph_optimized :optimized and merged poses
centralizedxxx.g2o :merged and optimized poses

Data/first_crash

You can use distributed_mapper to optimize them and get optimized result, then use g2oToKitti for visualization.

distributedmapping's People

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