{"id":20690887,"url":"https://github.com/rybandrei2014/obstacle_processor","last_synced_at":"2025-04-22T16:58:45.529Z","repository":{"id":111887297,"uuid":"134177136","full_name":"rybandrei2014/obstacle_processor","owner":"rybandrei2014","description":"ROS package for obstacle segmentation in a point cloud scene","archived":false,"fork":false,"pushed_at":"2020-01-07T20:44:58.000Z","size":20,"stargazers_count":15,"open_issues_count":0,"forks_count":6,"subscribers_count":0,"default_branch":"master","last_synced_at":"2025-03-29T16:51:16.000Z","etag":null,"topics":["catkin-pkg","catkin-workspace","cmake","cpp","kinect","kinect-v2","kinectv2","object-detection","object-recognition","obstacle-detection","obstacle-processor","obstacle-segmentation","rgb-d","rgb-d-data","ros","ros-kinetic","ros-node","ros-packages","segmentation","xml"],"latest_commit_sha":null,"homepage":null,"language":"C++","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/rybandrei2014.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null}},"created_at":"2018-05-20T18:44:59.000Z","updated_at":"2025-01-19T07:05:16.000Z","dependencies_parsed_at":null,"dependency_job_id":"bc2b3ddc-0885-476b-867b-60f7ea73f241","html_url":"https://github.com/rybandrei2014/obstacle_processor","commit_stats":null,"previous_names":["rybandrei2014/obstacle_processor"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rybandrei2014%2Fobstacle_processor","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rybandrei2014%2Fobstacle_processor/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rybandrei2014%2Fobstacle_processor/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/rybandrei2014%2Fobstacle_processor/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/rybandrei2014","download_url":"https://codeload.github.com/rybandrei2014/obstacle_processor/tar.gz/refs/heads/master","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":250284781,"owners_count":21405295,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","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":["catkin-pkg","catkin-workspace","cmake","cpp","kinect","kinect-v2","kinectv2","object-detection","object-recognition","obstacle-detection","obstacle-processor","obstacle-segmentation","rgb-d","rgb-d-data","ros","ros-kinetic","ros-node","ros-packages","segmentation","xml"],"created_at":"2024-11-16T23:14:42.206Z","updated_at":"2025-04-22T16:58:45.508Z","avatar_url":"https://github.com/rybandrei2014.png","language":"C++","readme":"# Obstacle_processor\nROS package for obstacle segmentation in a point cloud scene.\n## Installation\n* Before you install the package, you have to configure your RGB-D sensor and calibrate it. You can also run this package offline i.e. streaming point cloud ROS topic from .bag file.\n* Clone the repository inside **src/** directory of your catkin workspace\n```bash\nmkdir obstacle_processor\ncd obstacle_processor/\ngit clone name_of_repository\n```\n* Run CMake to compile source code\n```bash\ncatkin_make\n```\n* Source your workspace\n```bash\nsource catkin_ws/devel/setup.bash\n```\n* Setup your robot platform on a ground and remove the all objects in front of it for calibration purposes and run calibration node\n```bash\nroslaunch obstacle_processor calibration.launch\n```\n* Now you can run **obstacle_processor** detection algorithm by either of 5 launch commands (two last commands launch **obstacle_processor_node** along with **kinect2_bridge** package from \u003ca href=\"https://github.com/code-iai/iai_kinect2\"\u003eiai_kinect2\u003c/a\u003e package, but can be replaced for whatever bridge package compatible with your RGB-D sensor that produces point cloud ROS topic)\n```bash\nroslaunch obstacle_processor obstacle_processor.launch\n```\nor\n```bash\nroslaunch obstacle_processor obstacle_processor_rviz.launch\n```\nor\n```bash\nroslaunch obstacle_processor obstacle_processor_rviz_debug.launch\n```\nor\n```bash\nroslaunch obstacle_processor obstacle_processor_launch_all.launch\n```\nor\n```bash\nroslaunch obstacle_processor obstacle_processor_launch_all_rviz.launch\n```\n\n## References\nThe project was done as a part of research during \u003ca href=\"https://www.vutbr.cz/www_base/zav_prace_soubor_verejne.php?file_id=172947\"\u003ebachelor thesis\u003c/a\u003e\n### License\nMIT\n### Citation\nIf you use the repo in personal project or research, please cite it as follows:\n\n**RYBIN, A. Detekce překážek za použití kamerového 3D skeneru. Brno: Vysoké učení technické v Brně, Fakulta strojního inženýrství, 2018.**\n\n\nCopyright © 2017 Andrei Rybin\n","funding_links":[],"categories":[],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frybandrei2014%2Fobstacle_processor","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Frybandrei2014%2Fobstacle_processor","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Frybandrei2014%2Fobstacle_processor/lists"}