{"id":18439406,"url":"https://github.com/idiap/ttgo","last_synced_at":"2025-10-04T16:14:34.399Z","repository":{"id":37412038,"uuid":"505756195","full_name":"idiap/ttgo","owner":"idiap","description":"A PyTorch implementation of TTGO algorithm and the applications presented in the paper \"Tensor Train for Global Optimization Problems in Robotics\"","archived":false,"fork":false,"pushed_at":"2024-11-05T08:23:27.000Z","size":17281,"stargazers_count":18,"open_issues_count":0,"forks_count":3,"subscribers_count":5,"default_branch":"main","last_synced_at":"2025-03-06T03:04:23.721Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Jupyter Notebook","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/idiap.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":"COPYING","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":"2022-06-21T08:30:04.000Z","updated_at":"2025-01-24T00:58:49.000Z","dependencies_parsed_at":"2024-11-05T09:22:32.957Z","dependency_job_id":"0331873a-4f1b-465d-8f2b-90267faefc9d","html_url":"https://github.com/idiap/ttgo","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/idiap%2Fttgo","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/idiap%2Fttgo/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/idiap%2Fttgo/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/idiap%2Fttgo/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/idiap","download_url":"https://codeload.github.com/idiap/ttgo/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247732679,"owners_count":20986901,"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":"2024-11-06T06:24:39.996Z","updated_at":"2025-10-04T16:14:29.352Z","avatar_url":"https://github.com/idiap.png","language":"Jupyter Notebook","funding_links":[],"categories":[],"sub_categories":[],"readme":"# TTGO: Tensor Train for Global Optimization Problems in Robotics\n\nA PyTorch implementation of TTGO algorithm and the applications presented in the paper \"Tensor Train for Global Optimization Problems in Robotics \"\n\nWebsite: https://sites.google.com/view/ttgo/home\n\nPaper: https://arxiv.org/pdf/2206.05077.pdf\n\n### Pre-requistes\n- Install the tntorch library from: https://github.com/rballester/tntorch (pip install tntorch)\n- Pybullet (only required for visualization of robotics applications): https://pypi.org/project/pybullet/\n- RoMa (only required robotic applications; for quarternion calculations): https://naver.github.io/roma/\n\n### Overview\n- *./ttgo.py*: the TTGO algorithm is defined in this class\n- *./function_optimization/*: includes the application of ttgo for optimization of several benchmark functions\n  - Recommendation: try these notebooks first to understand the approach\n- *./toy_robots/*: application of ttgo for simple toy models of robotics problems (planar manipulator IK and reaching tasks)\n- *./manipulator/*: application of ttgo for IK and reaching tasks with some standard manipulators\n\nNote: All the implementations are fully compatible for use with GPU. For faster computation, it is highly recommended to use GPU\n\nFor any questions, contact the author Suhan Shetty \u003csuhan.shetty@idiap.ch\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fidiap%2Fttgo","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fidiap%2Fttgo","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fidiap%2Fttgo/lists"}