{"id":19855152,"url":"https://github.com/leggedrobotics/terrain-generator","last_synced_at":"2025-07-07T13:34:42.295Z","repository":{"id":191740304,"uuid":"684755725","full_name":"leggedrobotics/terrain-generator","owner":"leggedrobotics","description":null,"archived":false,"fork":false,"pushed_at":"2024-05-31T00:15:22.000Z","size":34689,"stargazers_count":181,"open_issues_count":6,"forks_count":22,"subscribers_count":6,"default_branch":"main","last_synced_at":"2025-04-06T20:46:29.696Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/leggedrobotics.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"LICENSE","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,"publiccode":null,"codemeta":null}},"created_at":"2023-08-29T19:38:49.000Z","updated_at":"2025-04-04T06:28:44.000Z","dependencies_parsed_at":null,"dependency_job_id":"af5ebd68-c8a3-4ee6-85fc-e16e8988aabb","html_url":"https://github.com/leggedrobotics/terrain-generator","commit_stats":null,"previous_names":["leggedrobotics/terrain-generator"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/leggedrobotics%2Fterrain-generator","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/leggedrobotics%2Fterrain-generator/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/leggedrobotics%2Fterrain-generator/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/leggedrobotics%2Fterrain-generator/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/leggedrobotics","download_url":"https://codeload.github.com/leggedrobotics/terrain-generator/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":251969265,"owners_count":21673183,"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":[],"created_at":"2024-11-12T14:11:51.322Z","updated_at":"2025-05-02T01:30:40.475Z","avatar_url":"https://github.com/leggedrobotics.png","language":"Python","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Terrain Generator\nThis is a automated terrain geneartor tool using [wave function collapse](https://github.com/mxgmn/WaveFunctionCollapse) method.\n\nThis is used in the paper, [Learning to walk in confined spaces using 3D representation](https://takahiromiki.com/publication-posts/learning-to-walk-in-confined-spaces-using-3d-representation/)\n\n[Project page](https://takahiromiki.com/publication-posts/learning-to-walk-in-confined-spaces-using-3d-representation/), [arxiv](https://arxiv.org/abs/2403.00187), [Youtube](https://youtu.be/QAwBoN55p9I)\n\n![Confined Terrain Generation](doc/confined-terrain-generation.gif)\n\n## Tiling meshes\nIt checks the connectivity of each mesh parts and connect them.\n\u003cp float=\"left\"\u003e\n  \u003cimg src=\"doc/tiling.gif\" width=\"49%\" /\u003e\n  \u003cimg src=\"doc/different-terrains.gif\" width=\"49%\" /\u003e \n\u003c/p\u003e\n\n\n# Install\nIf you're using conda, create env with the following command.\n```bash\nconda env create -f environment.yaml\npip install -e .\n```\n\n# Usage\nTo run a testing script run as follows.\n```bash\nconda activate wfc\npython3 examples/generate_with_wfc.py\n```\nThis will first generate all configured meshes and then build different combinations.\nOnce the mesh is generated, it is stored as cache and reused for the next time.\n\nYou can make your own config to generate different terrians.\n\n# Citation\nPlease cite the following paper if you use this software.\n\n```\n@article{miki2024learning,\n  title={Learning to walk in confined spaces using 3D representation},\n  author={Miki, Takahiro and Lee, Joonho and Wellhausen, Lorenz and Hutter, Marco},\n  journal={arXiv preprint arXiv:2403.00187},\n  year={2024}\n}\n```\n\n# Config\nTODO\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fleggedrobotics%2Fterrain-generator","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fleggedrobotics%2Fterrain-generator","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fleggedrobotics%2Fterrain-generator/lists"}