matlab-deep-learning/pretrained-dlCHOMP
Pretrained networks for Deep-Learning-Based Covariant Hamiltonian Optimization for Motion Planning (DLCHOMP) of robotic manipulators for MATLAB®
This project provides pre-trained deep learning networks to accelerate robot motion planning, helping roboticists and automation engineers quickly generate initial trajectory guesses for robotic manipulators moving from a start to a goal configuration within an environment with spherical obstacles. You provide the desired start and end positions and the obstacle layout, and it outputs a more efficient initial trajectory that can then be optimized. This is ideal for those working with MATLAB's Robotics System Toolbox.
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Use this if you need to quickly generate efficient initial motion plans for robotic manipulators navigating spherical obstacles, especially when working with MATLAB.
Not ideal if you require motion planning for non-spherical obstacles or if you are not working within the MATLAB environment.
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MATLAB
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Last pushed
May 01, 2024
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