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DIVE

Deep Inertial-Only Velocity Aided Estimation for Quadrotors


Environment

conda create -f environment.yaml

or

conda create -n dive python=3.10
conda activate dive
conda install nvidia/label/cuda-11.8.0::cuda-toolkit
pip install torch==2.6.0 torchvision==0.21.0 torchaudio==2.6.0 --index-url https://download.pytorch.org/whl/cu118
pip install lightning tensorboard numpy h5py matplotlib pandas scipy seaborn torchviz pymap3d
pip install git+https://github.com/decargroup/pymlg.git
pip install git+https://github.com/decargroup/navlie.git

the navlie package will install pymlg as a dependency.


DIDO Dataset

git clone https://github.com/sejun-ahn/DIDO

the original repository is here (@zhangkunyi/DIDO)

set the directory at network/train.py


Train

python network/train.py

the trained checkpoints are at lightning_logs/validation_checkpoints

tensorboard --logdir .

and you can check the tensorboard logs

Validate/Test

python syn_pseudo/velocity_regressor_dido.py

the estimated results are at <root_dir>/<filter_output_folder/<file_target>/<filter_output_name>

Visualize

python visualizer/plot_syn_dido.py

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