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# Sphinx build info version 1 | ||
# This file hashes the configuration used when building these files. When it is not found, a full rebuild will be done. | ||
config: 220a603646fe45b7c5d09365057b4547 | ||
tags: 645f666f9bcd5a90fca523b33c5a78b7 |
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################################################## | ||
Multi-modal elevation mapping's documentation | ||
################################################## | ||
Welcome to elevation mapping documentation | ||
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.. image:: https://github.com/leggedrobotics/elevation_mapping_semantic_cupy/actions/workflows/python-tests.yml/badge.svg | ||
:target: https://github.com/leggedrobotics/elevation_mapping_semantic_cupy/actions/workflows/python-tests.yml/badge.svg | ||
:alt: python tests | ||
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.. image:: https://github.com/leggedrobotics/elevation_mapping_semantic_cupy/actions/workflows/documentation.yml/badge.svg | ||
:target: https://github.com/leggedrobotics/elevation_mapping_semantic_cupy/actions/workflows/documentation.yml/badge.svg | ||
:alt: documentation | ||
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Index | ||
--------------- | ||
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| :doc:`getting_started/introduction` - What is elevation mapping cupy | ||
| :doc:`getting_started/installation` - How to install the elevation map | ||
| :doc:`getting_started/tutorial` - How to launch the first elevation map | ||
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This is a ROS package for elevation mapping on GPU. The elevation mapping code is written in python and uses cupy for GPU computation. The | ||
plane segmentation is done independently and runs on CPU. When the plane segmentation is generated, local convex approximations of the | ||
terrain can be efficiently generated. | ||
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.. image:: ../media/main_repo.png | ||
:alt: Elevation map examples | ||
.. image:: ../media/main_mem.png | ||
:alt: Overview of the project | ||
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Citing | ||
--------------- | ||
If you use the elevation mapping cupy, please cite the following paper: | ||
Elevation Mapping for Locomotion and Navigation using GPU | ||
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.. hint:: | ||
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Elevation Mapping for Locomotion and Navigation using GPU `Link <https://arxiv.org/abs/2204.12876>`_ | ||
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Takahiro Miki, Lorenz Wellhausen, Ruben Grandia, Fabian Jenelten, Timon Homberger, Marco Hutter | ||
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.. code-block:: | ||
@misc{mikielevation2022, | ||
doi = {10.48550/ARXIV.2204.12876}, | ||
author = {Miki, Takahiro and Wellhausen, Lorenz and Grandia, Ruben and Jenelten, Fabian and Homberger, Timon and Hutter, Marco}, | ||
keywords = {Robotics (cs.RO), FOS: Computer and information sciences, FOS: Computer and information sciences}, | ||
title = {Elevation Mapping for Locomotion and Navigation using GPU}, | ||
publisher = {International Conference on Intelligent Robots and Systems (IROS)}, | ||
year = {2022}, | ||
} | ||
Multi-modal elevation mapping if you use color or semantic layers | ||
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.. hint:: | ||
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MEM: Multi-Modal Elevation Mapping for Robotics and Learning `Link <https://arxiv.org/abs/2309.16818v1>`_ | ||
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Gian Erni, Jonas Frey, Takahiro Miki, Matias Mattamala, Marco Hutter | ||
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.. code-block:: | ||
@misc{Erni2023-bs, | ||
title = "{MEM}: {Multi-Modal} Elevation Mapping for Robotics and Learning", | ||
author = "Erni, Gian and Frey, Jonas and Miki, Takahiro and Mattamala, Matias and Hutter, Marco", | ||
publisher = {International Conference on Intelligent Robots and Systems (IROS)}, | ||
year = {2023}, | ||
} |
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Cuda installation | ||
================================================================== | ||
.. _cuda_installation: | ||
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CUDA | ||
------------------------------------------------------------------- | ||
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You can download CUDA10.2 from `here <https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin>`_. | ||
You can follow the instruction. | ||
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.. code-block:: bash | ||
wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/cuda-ubuntu1804.pin | ||
sudo mv cuda-ubuntu1804.pin /etc/apt/preferences.d/cuda-repository-pin-600 | ||
sudo apt-key adv --fetch-keys https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/7fa2af80.pub | ||
sudo add-apt-repository "deb https://developer.download.nvidia.com/compute/cuda/repos/ubuntu1804/x86_64/ /" | ||
sudo apt-get update | ||
sudo apt-get -y install cuda | ||
cuDNN | ||
------------------------------------------------------------------- | ||
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You can download specific version from `here <https://developer.download.nvidia.com/compute/machine-learning/repos/ubuntu1804/x86_64/>`_. | ||
For example, the tested version is with `libcudnn8_8.0.0.180-1+cuda10.2_amd64.deb`. | ||
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Then install them using the command below. | ||
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.. code-block:: bash | ||
sudo dpkg -i libcudnn8_8.0.0.180-1+cuda10.2_amd64.deb | ||
sudo dpkg -i libcudnn8-dev_8.0.0.180-1+cuda10.2_amd64.deb | ||
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