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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Robotics with GPU computing
| Date | Stars |
|---|---|
| 2026-07-24 | 1060 |
| 2026-07-25 | 1060 |
| 2026-07-28 | 1060 |
| 2026-07-30 | 1060 |
| 2026-08-06 | 1060 |
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<p align="center">
<img src="https://raw.githubusercontent.com/neka-nat/cupoch/master/docs/_static/cupoch_logo.png" width="320" />
</p>
# Robotics with GPU computing
[](https://github.com/neka-nat/cupoch/actions/workflows/ubuntu.yml/badge.svg)
[](https://github.com/neka-nat/cupoch/actions/workflows/windows.yml/badge.svg)[](https://badge.fury.io/py/cupoch)
[](https://pepy.tech/project/cupoch)
[](https://xscode.com/neka-nat/cupoch)
<a href="https://www.buymeacoffee.com/nekanat" target="_blank"><img src="https://cdn.buymeacoffee.com/buttons/v2/default-yellow.png" alt="Buy Me A Coffee" width="150" height="40" ></a>
Cupoch is a library that implements rapid 3D data processing for robotics using CUDA.
The goal of this library is to implement fast 3D data computation in robot systems.
For example, it has applications in SLAM, collision avoidance, path planning and tracking.
This repository is based on [Open3D](https://github.com/intel-isl/Open3D).
## Core Features
* 3D data processing and robotics computation using CUDA
* KNN
* [WIP] [Optimizing LBVH-Construction and Hierarchy-Traversal to accelerate kNN Queries on Point Clouds using the GPU](https://epub.uni-bayreuth.de/5288/1/cgf.14177.pdf)
* [flann](https://github.com/flann-lib/flann)
* Point cloud registration
* ICP
* Generalized ICP
* [Symmetric ICP](https://gfx.cs.princeton.edu/pubs/Rusinkiewicz_2019_ASO/symm_icp.pdf) (Implemented by [@eclipse0922](https://github.com/eclipse0922))
* [Colored Point Cloud Registration](https://ieeexplore.ieee.org/document/8237287)
* [Fast Global Registration](http://vladlen.info/papers/fast-global-registration.pdf)
* [FilterReg](https://arxiv.org/abs/1811.10136)
* Point cloud features
* FPFH
* SHOT
* Point cloud keypoints
* ISS
* Point cloud clustering
* [G-DBSCAN: A GPU Accelerated Algorithm for Density-based Clustering](https://www.sciencedirect.com/science/article/pii/S1877050913003438)
* Point cloud/Triangle mesh filtering, down sampling
* IO
* Several file types(pcd, ply, stl, obj, urdf)
* ROS message
* Create Point Cloud from Laser Scan or RGBD Image
* Visual Odometry
* [Real-time visual odometry from dense RGB-D images](https://ieeexplore.ieee.org/document/6130321)
* [Robust Odometry Estimation for RGB-D Cameras](https://ieeexplore.ieee.org/document/6631104)
* Kinect Fusion
* Stereo Matching
* Collision checking
* Occupancy grid
* Distance transform
* [Parallel Banding Algorithm to Compute Exact Distance Transform with the GPU](https://www.comp.nus.edu.sg/~tants/pba.html)
* Path finding on graph structure
* Path planning for collision avoidance
* Support memory pool and managed allocators
* Interactive GUI (OpenGL CUDA interop and [imgui](https://github.com/ocornut/imgui))
* Interoperability between cupoch 3D data and [DLPack](https://github.com/dmlc/dlpack)(Pytorch, Cupy,...) data structure
## Installation
This library is packaged under 64 Bit Ubuntu Linux 24.04 and CUDA 12.9.
You can install cExcerpt of 10,307 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:aa5133d3e94df1ee, topic:robotics, topic:ros, desc:robotics
matched fp:aa5133d3e94df1ee, topic:gpu, topic:cuda