Use python SCRIPT_NAME -d FILE_PATH,FILE_PATH,... [OPTIONS] to run the program.

Example Usage

python -d ./Baxter_14_22x22x21.npz -l 0.00001

python -d ./Baxter_14_22x22x21.npz -s 90000 -p -r ./checkpoints/08102020180642/


The script files provided allow the user to train the networks and predict output using trained network checkpoints.

The scripts provided are:


Below are a list of command line parameters:



The files provided are saved scipy.sparse.csr_matrix objects. The first Num-Features columns are the start configuration followed by end configuration joint values for the robot. The remaining columns are label values for the Label-Dims volume grid space converted from xyz coorinates to a linear order with x being the most significant axis and z the least significant.

File name format: Robot_Num-Features_Label-Dims.npz

Software and Libraries

The following are a list of software and libraries used for the project: