{"id":13436217,"url":"https://github.com/yzrobot/adaptive_clustering","last_synced_at":"2026-01-18T15:04:02.283Z","repository":{"id":83908131,"uuid":"172483575","full_name":"yzrobot/adaptive_clustering","owner":"yzrobot","description":"[ROS package] Lightweight and Accurate Point Cloud 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unexpected eof while reading","robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":false,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["clustering","point-cloud","point-cloud-segmentation","ros","velodyne"],"created_at":"2024-07-31T03:00:45.581Z","updated_at":"2026-01-18T15:04:02.254Z","avatar_url":"https://github.com/yzrobot.png","language":"C++","funding_links":[],"categories":["C++"],"sub_categories":[],"readme":"# Adaptive Clustering: A lightweight and accurate point cloud clustering method #\n\n[![Build Status](https://travis-ci.org/yzrobot/adaptive_clustering.svg?branch=master)](https://travis-ci.org/yzrobot/adaptive_clustering)\n[![Codacy Badge](https://api.codacy.com/project/badge/Grade/61a01a79a7ac41fd9deded9050ef6030)](https://www.codacy.com/app/yzrobot/adaptive_clustering?utm_source=github.com\u0026amp;utm_medium=referral\u0026amp;utm_content=yzrobot/adaptive_clustering\u0026amp;utm_campaign=Badge_Grade)\n[![License](https://img.shields.io/badge/License-BSD%203--Clause-green.svg)](https://opensource.org/licenses/BSD-3-Clause)\n\n[![YouTube Video](https://img.youtube.com/vi/rmPn7mWssto/0.jpg)](https://www.youtube.com/watch?v=rmPn7mWssto)\n\n## Changelog ##\n\n*   **\\[Apr 14, 2022\\]:** Two new branches, [gpu](https://github.com/yzrobot/adaptive_clustering/tree/gpu) and [agx](https://github.com/yzrobot/adaptive_clustering/tree/agx), have been created for GPU-based implementations:\n    *   [gpu](https://github.com/yzrobot/adaptive_clustering/tree/gpu) is based on [PCL-GPU](https://pcl.readthedocs.io/projects/tutorials/en/master/#gpu) and has been tested with an NVIDIA TITAN Xp.\n    *   [agx](https://github.com/yzrobot/adaptive_clustering/tree/agx) is based on [CUDA-PCL](https://github.com/NVIDIA-AI-IOT/cuda-pcl) and has been tested with an NVIDIA Jetson AGX Xavier.\n\n*   **\\[Feb 25, 2019\\]:** A new branch, [devel](https://github.com/yzrobot/adaptive_clustering/tree/devel), faster (by downsampling) and better (by merging clusters split by nested regions and on the z-axis).\n\n## How to build ##\n```sh\ncd ~/catkin_ws/src/\ngit clone https://github.com/yzrobot/adaptive_clustering.git\ncd ~/catkin_ws\ncatkin_make\n```\n\n## Citation ##\nIf you are considering using this code, please reference the following:\n```\n@article{yz19auro,\n   author = {Zhi Yan and Tom Duckett and Nicola Bellotto},\n   title = {Online learning for 3D LiDAR-based human detection: Experimental analysis of point cloud clustering and classification methods},\n   journal = {Autonomous Robots},\n   year = {2019}\n}\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyzrobot%2Fadaptive_clustering","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fyzrobot%2Fadaptive_clustering","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fyzrobot%2Fadaptive_clustering/lists"}