{"id":19134312,"url":"https://github.com/um-arm-lab/escher_openrave_cpp","last_synced_at":"2025-08-31T12:07:46.802Z","repository":{"id":79650841,"uuid":"100801299","full_name":"UM-ARM-Lab/escher_openrave_cpp","owner":"UM-ARM-Lab","description":"OpenRAVE C++ plugin for Escher Robot","archived":false,"fork":false,"pushed_at":"2020-05-29T14:19:46.000Z","size":1124382,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":7,"default_branch":"master","last_synced_at":"2025-02-22T17:47:42.908Z","etag":null,"topics":[],"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/UM-ARM-Lab.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,"publiccode":null,"codemeta":null}},"created_at":"2017-08-19T14:54:08.000Z","updated_at":"2020-05-29T14:19:49.000Z","dependencies_parsed_at":"2023-05-14T09:00:31.598Z","dependency_job_id":null,"html_url":"https://github.com/UM-ARM-Lab/escher_openrave_cpp","commit_stats":null,"previous_names":[],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/UM-ARM-Lab/escher_openrave_cpp","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UM-ARM-Lab%2Fescher_openrave_cpp","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UM-ARM-Lab%2Fescher_openrave_cpp/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UM-ARM-Lab%2Fescher_openrave_cpp/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UM-ARM-Lab%2Fescher_openrave_cpp/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/UM-ARM-Lab","download_url":"https://codeload.github.com/UM-ARM-Lab/escher_openrave_cpp/tar.gz/refs/heads/master","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/UM-ARM-Lab%2Fescher_openrave_cpp/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":272977020,"owners_count":25025044,"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","status":"online","status_checked_at":"2025-08-31T02:00:09.071Z","response_time":79,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"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":[],"created_at":"2024-11-09T06:26:11.786Z","updated_at":"2025-08-31T12:07:46.786Z","avatar_url":"https://github.com/UM-ARM-Lab.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# escher_openrave_cpp\nOpenRAVE C++ plugin for Escher Robot to run contact planner and experiment for the paper: \"Robust Humanoid Contact Planning with Learned Zero- and One-Step Capturability Prediction\" in RA-L 2020.\n\n`escher_cpp_motion_planner_interface.py` is the main testing script used to run experiments. It will call the corresponding functions in `EscherMotionPlanning.cpp` through OpenRAVE cpp interface with configurations shown in `escher_openrave_cpp_wrapper.py`. The contact planner is described in `ContactSpacePlanning.cpp`.\n\n# Dependency\n\n* [OpenRAVE 0.9.0](https://github.com/rdiankov/openrave/tree/v0.9.0)\n* ROS Melodic/Kinetic/Indigo\n* [frugally-deep](https://github.com/Dobiasd/frugally-deep)\n* Tensorflow 1.40\n* [comps](https://github.com/UM-ARM-Lab/comps)\n* [SL](https://github.com/UM-ARM-Lab/SL_and_momopt)\n\n# Setup\n\n1. Install ROS, OpenRAVE, Tensorflow (with C++ API), and frugally-deep\n2. Create a catkin workspace, and put `escher_openrave_cpp`, comps and SL under the same catkin workspace.\n3. `catkin_make` to build the code.\n\n# Usage\n\n* `surface_source`: The source of the environment in planning. The user can create new environment by adding new options in `update_environment` function in `environment_handler_2.py`.\u003cbr/\u003e\n  `capture_test_env_3`: Narrow flat corridor environment.\u003cbr/\u003e\n  `capture_test_env_4`: One-wall rubble environment.\u003cbr/\u003e\n  `capture_test_env_5`: Oil platform environment.\u003cbr/\u003e\n  `load_from_data`: Load environment object file stored using `pickle` from path specified by `environment_path` parameter.\n\n* `environment_path`: The folder which contains the stored environment object file.\n* `start_env_id` and `end_env_id`: The first and last environment object file id loaded in the process.\n\n\nExample Usage:\n```\npython escher_cpp_motion_planner_interface.py surface_source capture_test_env_4 start_env_id 0 end_env_id 0\n```\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fum-arm-lab%2Fescher_openrave_cpp","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fum-arm-lab%2Fescher_openrave_cpp","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fum-arm-lab%2Fescher_openrave_cpp/lists"}