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Repository Summary
Checkout URI | https://github.com/miroboticslab/cyberdog_miloc.git |
VCS Type | git |
VCS Version | rolling |
Last Updated | 2024-09-11 |
Dev Status | UNMAINTAINED |
CI status | No Continuous Integration |
Released | UNRELEASED |
Tags | No category tags. |
Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Packages
Name | Version |
---|---|
cyberdog_miloc | 0.0.0 |
README
CYBERDOG_MILOC
cyberdog_miloc is a visual mapping and localization module based on a trinocular camera system, used for visual mapping and navigation. During the mapping process, it utilizes robot poses output from MIVINS and images for sparse reconstruction. During the navigation process, it provides the pose located in the map。
Prerequisites
system
Ubuntu 18.04/20.04
Ros
ROS2:galactic
Deep learning
Depend on Jetpack 4.6,include CUDA 10.2、cuDNN 8.2.1、TensorRT 8.0.1
others
- OpenCV 4.2.0
- yaml-cpp
- ceres
- eigen3
- colmap 4.7: in cyberdog_miloc/lib/colmap
Build Cyberdog_miloc
colcon build --merge-install --install-base /opt/ros2/cyberdog
Miloc Models
Miloc models needs to be manually updated from GitHub
# delete old models
rm -rf /SSD/miloc/models/*
# down load 3 models (global_models.trt local_model.trt match_models.trt)
# from GitHub to /SSD/miloc/models/
# create version file and add version number
touch /SSD/miloc/models/version.toml
echo 'version = "2.0"' > /SSD/miloc/models/version.toml
RUN
source /opt/ros2/cyberdog/setup.bash
ros2 launch cyberdog_miloc miloc_server_launch.py
miloc_server will check and update the deep learning model when it is connected to the network.
- Mapping mode
depend on cyberdog_occmap、cyberdog_mivins、and camera images
- Reloc mode
depend on camera images
CONTRIBUTING
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