A Modular Framework for Robot Planning, Control, and Deployment (RPC). It is designed to integrate multiple physics-based simulators, planning and control modules, visualization tools, plotting and logging utilities, and operator interfaces for robotic systems.
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Issue on DracoDataManager.py for meshcat visualization #1
To use the meshcat visualization tool for a real-time visualization/experiment replay, pinocchio library needs to be installed in a conda environment through conda-forge. This could prevent rebuilding the controller using CMake, due to the libboost_python${VERSION}.so discrepancy between the c++ and python versions of pinocchio library.
A hacky solution is first building a c++ library and then installing the python version of pinocchio in a conda environment.
If you need to rebuild the c++ library, then erase the current conda environment and recreate the environment.
One possible solution is to create another virtual environment for the python version of pinocchio. Then, if you want to visualize a robot using meshcat, just executing the DracoDataManager.py script would be enough.
To use the meshcat visualization tool for a real-time visualization/experiment replay, pinocchio library needs to be installed in a conda environment through conda-forge. This could prevent rebuilding the controller using CMake, due to the libboost_python${VERSION}.so discrepancy between the c++ and python versions of pinocchio library.
A hacky solution is first building a c++ library and then installing the python version of pinocchio in a conda environment.
If you need to rebuild the c++ library, then erase the current conda environment and recreate the environment.