TaichiSLAM

This project is a 3D Dense mapping backend library of SLAM based Taichi-Lang, designed for the aerial swarm.

Demo video

Intro

Taichi is an efficient domain-specific language (DSL) designed for computer graphics (CG), which can be adopted for high-performance computing on mobile devices. Thanks to the connection between CG and robotics, we can adopt this powerful tool to accelerate the development of robotics algorithms.

In this project, I am trying to take advantages of Taichi, including parallel optimization, sparse computing, advanced data structures and CUDA acceleration. The original purpose of this project is to reproduce dense mapping papers, including Octomap, Voxblox, Voxgraph etc.

Note: This project is only backend of 3d dense mapping. For full SLAM features including real-time state estimation, pose graph optimization, depth generation, please take a look on VINS and my fisheye fork of VINS.

Demos

Octomap/Occupy[1] map at different accuacy:

<img src="./docs/octomap1.png" alt="drawing" style="width:400px;"/> <img src="./docs/octomap2.png" alt="drawing" style="width:400px;"/> <img src="./docs/octomap3.png" alt="drawing" style="width:400px;"/>

Truncated signed distance function (TSDF) [2]: Surface reconstruct by TSDF (not refined) Occupy map and slice of original TSDF

Usage

Install taichi via pip

pip install taichi

Download TaichiSLAM to your dev folder and add them to PYTHONPATH

git clone https://github.com/xuhao1/TaichiSLAM

Integration with ROS

Running TaichiSLAMNode (require ROS), download dataset at this link.

# Terminal 1
rosbag play taichislam-realsense435.bag
# Terminal 2
roslaunch launch/taichislam-d435.launch show:=true

Generation topology skeleton graph [4]

This demo generate topological skeleton graph from TSDF This demo does not require ROS. Nvidia GPU is recommend for better performance.

pip install -r requirements.txt
python tests/gen_topo_graph.py

This shows the polyhedron

De-select the mesh in the options to show the skeleton

Bundle Adjustment (In development)

Roadmap

Paper Reproduction

• [x] Octomap
• [x] Voxblox
• [ ] Voxgraph

Features

Mapping

• [x] Octotree occupancy map [1]
• [x] TSDF [2]
• [x] Incremental ESDF [2]
• [x] Submap [3]
  • [ ] Octomap
  • [x] TSDF
  • [ ] ESDF
• [x] Topology skeleton graph generation [4]
  • [x] TSDF
  • [ ] Pointcloud/Octomap
• [ ] Loop Detection

MISC

• [x] ROS/RVIZ/rosbag interface
• [x] 3D occupancy map visuallizer
• [x] 3D TSDF/ESDF map visuallizer
• [ ] Export to C/C++
• [ ] Benchmark

Know issue

Memory issue on ESDF generation, debugging...

References

[1] Hornung, Armin, et al. "OctoMap: An efficient probabilistic 3D mapping framework based on octrees." Autonomous robots 34.3 (2013): 189-206.

[2] Oleynikova, Helen, et al. "Voxblox: Incremental 3d euclidean signed distance fields for on-board mav planning." 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). IEEE, 2017.

[3] Reijgwart, Victor, et al. "Voxgraph: Globally consistent, volumetric mapping using signed distance function submaps." IEEE Robotics and Automation Letters 5.1 (2019): 227-234.

[4] Chen, Xinyi, et al. "Fast 3D Sparse Topological Skeleton Graph Generation for Mobile Robot Global Planning." arXiv preprint arXiv:2208.04248 (2022).

LICENSE

LGPL