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ganlumomo / MultiLayerMapping

Multi-Task Learning for Scalable and Dense Multi-Layer Bayesian Map Inference
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bayesian-inference semantic-mapping traversability-mapping

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MultiLayerMapping

Multi-Task Learning for Scalable and Dense Multi-Layer Bayesian Map Inference

Getting Started

Building with catkin

$mkdir -p ~/catkin_ws/src
$cd ~/catkin_ws/src
catkin_ws/src$ git clone https://github.com/ganlumomo/MultiLayerMapping.git
catkin_ws/src$ cd ..
catkin_ws$ catkin_make
catkin_ws$ source ~/catkin_ws/devel/setup.bash

Building using Intel C++ compiler (optional for efficiency)

catkin_ws$ source /opt/intel/compilers_and_libraries/linux/bin/compilervars.sh intel64
catkin_ws$ catkin_make -DCMAKE_C_COMPILER=icc -DCMAKE_CXX_COMPILER=icpc
catkin_ws$ source ~/catkin_ws/devel/setup.bash

Running the Toy Example

MultiLayerMapping/launch$ roslaunch semantics_static.launch

Running the Cassie Exp

MultiLayerMapping/launch$ roslaunch cassie_node.launch
MultiLayerMapping/rviz$ rosrun rviz rviz -d cassie.rviz

Relevant Publications

If you found this code useful, please cite the following:

Multi-Task Learning for Scalable and Dense Multi-Layer Bayesian Map Inference (PDF)

@ARTICLE{gan2022multi,
  title={Multitask Learning for Scalable and Dense Multilayer {Bayesian} Map Inference},
  author={Gan, Lu and Kim, Youngji and Grizzle, Jessy W and Walls, Jeffrey M and Kim, Ayoung and Eustice, Ryan M and Ghaffari, Maani},
  journal={IEEE Transactions on Robotics},
  year={2022},
  doi={10.1109/TRO.2022.3197106}
}

Bayesian Spatial Kernel Smoothing for Scalable Dense Semantic Mapping (PDF)

@ARTICLE{gan2020bayesian,
  author={Gan, Lu and Zhang, Ray and Grizzle, Jessy W. and Eustice, Ryan M. and Ghaffari, Maani},
  journal={IEEE Robotics and Automation Letters}, 
  title={Bayesian Spatial Kernel Smoothing for Scalable Dense Semantic Mapping}, 
  year={2020},
  volume={5},
  number={2},
  pages={790-797},
  doi={10.1109/LRA.2020.2965390}
}

Acknowledgement

This repo is mostly based on: