AI Decision System
Replayable, offline-verifiable records for AI-assisted go/no-go decisions: experiment promotions, typed model answers and human-approved actions.
robotic motion planning library
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Developer toolsPython · C++GitHub @hungpham2511Self-installOwner unconfirmed
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Read the full 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