{"id":19526655,"url":"https://github.com/zju-fast-lab/dftpav","last_synced_at":"2025-04-05T22:06:36.299Z","repository":{"id":48155650,"uuid":"516253341","full_name":"ZJU-FAST-Lab/Dftpav","owner":"ZJU-FAST-Lab","description":"A lightweight differential flatness-based trajectory planner for car-like robots","archived":false,"fork":false,"pushed_at":"2023-06-21T11:40:14.000Z","size":88537,"stargazers_count":382,"open_issues_count":9,"forks_count":89,"subscribers_count":23,"default_branch":"main","last_synced_at":"2025-03-29T20:09:51.708Z","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":"gpl-3.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/ZJU-FAST-Lab.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":"2022-07-21T06:34:02.000Z","updated_at":"2025-03-28T13:55:49.000Z","dependencies_parsed_at":"2024-11-11T01:21:24.802Z","dependency_job_id":null,"html_url":"https://github.com/ZJU-FAST-Lab/Dftpav","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/ZJU-FAST-Lab%2FDftpav","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZJU-FAST-Lab%2FDftpav/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZJU-FAST-Lab%2FDftpav/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/ZJU-FAST-Lab%2FDftpav/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/ZJU-FAST-Lab","download_url":"https://codeload.github.com/ZJU-FAST-Lab/Dftpav/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":247406087,"owners_count":20933803,"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":"2024-11-11T01:11:15.150Z","updated_at":"2025-04-05T22:06:36.265Z","avatar_url":"https://github.com/ZJU-FAST-Lab.png","language":"C++","funding_links":[],"categories":[],"sub_categories":[],"readme":"# Dftpav\n\nA lightweight **Spatial-Temporal** trajectory planner for car-like robots。\n\n## 0. Overview\n**Related Paper**: \n\nPlease cite the paper below if this repo helps you.\n\n- [An Efficient Spatial-Temporal Trajectory Planner for Autonomous Vehicles in Unstructured Environments](https://arxiv.org/abs/2208.13160), Zhichao Han, Yuwei Wu, Tong Li, Lu Zhang, Liuao Pei, Long Xu, Chengyang Li, Changjia Ma, Chao Xu, Shaojie Shen, Fei Gao.\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"figs/1.gif\" width = \"800\"/\u003e\n\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"figs/2.gif\" width = \"800\"/\u003e\n\u003c/p\u003e\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"figs/3.gif\" width = \"800\"/\u003e\n\u003c/p\u003e\n\n\n\n## 1. Setup\nAll the tests are conducted in the Linux environment on a computer equipped with an Intel Core i7-10700 CPU and a GeForce RTX 2060 GPU.\n\nMoreover, Our software is developed and tested in Ubuntu 18.04, 20.04 with ROS installed.\n\nROS can be installed here: [ROS Installation](http://wiki.ros.org/ROS/Installation).\n\n## 2. Build on ROS\n\n1. Install the dependence.\n\n   ```\n   sudo apt-get install libgoogle-glog-dev libdw-dev libopenblas-dev gfortran\n   ```\n   \n   We use [Protocol Buffers](https://developers.google.com/protocol-buffers/) for parameter configuration. For the installation guide, please refer to this [link](https://github.com/protocolbuffers/protobuf/blob/master/src/README.md).\n\n2. Create an empty new workspace and clone this repository to your workspace: \n\n   ```\n   cd ~/your_catkin_ws/src\n   git clone https://github.com/ZJU-FAST-Lab/Dftpav\n   cd ..\n   ```\n\n3. Compile it.\n\n   ```\n   catkin_make -DCMAKE_BUILD_TYPE=Release\n   ```\n\n## 3. Run\n\nOpen a new terminal window, `cd ` to `~/your_catkin_ws/` and type:\n\n```\nsource devel/setup.bash\n```\n\nThen, run the script:\n\n```\n./run.sh \n```\n\nThen, you can use the **2D Nav Goal** in **RVIZ** to trigger the planning.\n\nHere is an example:\n\n\u003cp align=\"center\"\u003e\n  \u003cimg src=\"figs/4.gif\" width = \"800\"/\u003e\n\u003c/p\u003e\n\n## 4. Licence\nThe source code is released under [GPLv3](http://www.gnu.org/licenses/) license.\n\n## 5. Maintaince\n\nFor any technical issue, please contact Zhichao HAN (zhichaohan@zju.edu.cn).\n\nFor commercial inquiries, please contact [Fei GAO](https://ustfei.com/) (fgaoaa@zju.edu.cn).\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzju-fast-lab%2Fdftpav","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fzju-fast-lab%2Fdftpav","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fzju-fast-lab%2Fdftpav/lists"}