Task and Motion Planning Library (TAMPL)

⚠ Warning: This library is still under development.

An all-in-one library for prototyping, benchmarking, and integrating task and motion planning algorithms into real-world systems, all powered by behavior trees.

Building Instructions

Prerequisites

Before building TAMPL from source, ensure that the necessary dependencies are installed.

For Linux (Ubuntu/Debian)

$ sudo apt install -y libboost-all-dev libeigen3-dev libzmq3-dev libsqlite3-dev

For macOS (using Homebrew)

$ brew install boost eigen zeromq sqlite

TAMPL also uses CPM.cmake to manage additional dependenices such as BehaviorTree.CPP, OMPL, and more. These dependencies can be found in dependencies.cmake.

Building from Source

Note: If you want to build TAMPL with Python bindings, you can skip this section and proceed to Python Bindings (Experimental)

Run the following commands from the repository's top-level directory to build TAMPL from source. The first build may take some time as all necessary dependencies will be downloaded and compiled.

$ mkdir build && cd build
$ cmake ..
$ make -j$(nproc)

Python Bindings (Experimental)

TAMPL also supports experimental Python bindings. To enable this, first set up a Python virtual environment and install the necessary dependencies:

$ python -m venv tampl_venv
$ source tampl_venv/bin/activate
$ pip install -r requirements.txt

Then, run the following command from the repository's top-level directory to build TAMPL along with its Python bindings from source:

$ pip install -v .

Running Examples

All the examples demonstrating TAMPL's capabilities can be found in the examples.