AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
翻译准备中
robotic motion planning library
翻译准备中
开发工具Python · C++GitHub @hungpham2511自行安装运营者未确认
试用过了吗? 点一下就好,无需登录。
个人 GitHub 账号下公开仓库的所有者可以登录并验证所有权,自行管理介绍,无需管理员批准。
登录并生成验证文件,在 30 分钟内将其提交到此仓库的默认分支。其他分支或分叉仓库中的文件无效。然后在下方检查文件,即可无需管理员批准直接管理项目。请保留文件以维持管理权限。
如需登录,将前往登录页面。登录后请回到此处,再次点击所选的验证按钮。
安装型项目无需部署域名也可验证。个人仓库可通过 GitHub 登录验证,组织仓库可使用上方的仓库验证文件。
制作者的介绍仅有上面的一句话。 更多详情请阅读仓库 README。 仓库 README ↗
正在加载完整 README。
查看完整 README ↗toppra: Time-Optimal Path Parameterization[!NOTE] Python support for the library will be dropped. Consider using the C++ version with bindings instead.
toppra is a library for computing the time-optimal path parametrization for robots subject to kinematic and dynamic constraints. In general, given the inputs:
p(s), s in [0, s_end];toppra returns the time-optimal path parameterization: s_dot (s), from which the fastest trajectory q(t) that satisfies the
given constraints can be found.
Documentation and tutorials are available here.
You can install the package with pip:
pip install toppra
To install from source for development:
pip install -e python
Please report any issues, questions or feature request via Github issues tracker.
Have a quick question? Try asking in our slack channel.
Pull Requests are welcome! Create a Pull Request and we will review your proposal!
toppra was originally developed by Hung
Pham (Eureka Robotics, former CRI
Group) and Phạm Quang Cường
(Eureka Robotics, CRI Group) with major contributions from talented
contributors:
If you have taken part in developing and supporting the library, feel free to add your name to the list.
The development is also generously supported by Eureka Robotics.
If you use this library for your research, we encourage you to