data_params.toml

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DataDir =  "${CoverageControl_ws}/lpac" # Absolute location
EnvironmentConfig = "${CoverageControl_ws}/lpac/params/coverage_control_params.toml" # Absolute location
 
# Only required for data generation using C++
# The generator requires a TorchVision JIT transformer model
# for resizing robot local maps on the GPU
# The python script for generating the model is located at
# CoverageControl/cppsrc/torch/resize.py
# resize.pt is also present for CNNMapSize of 32
TorchVisionTransformJIT = "./TorchVisionResize_32.pt" # Relative to DataDir
 
NumDataset = 1000
 
# Number of steps to take before data is stores
# This helps in creating a more diverse dataset
EveryNumSteps = 5
 
# The robots stop moving once the algorithm has converged
# Having some of these converged steps can help in stabilizing robot actions
ConvergedDataRatio = 0.02
 
# Resizing of maps and Sparsification of tensors are triggered every TriggerPostProcessing dataset
# This should be set based on RAM resources available on the system
TriggerPostProcessing = 100
 
CNNMapSize = 32
SaveAsSparseQ = true
NormalizeQ = true
 
[DataSetSplit]
TrainRatio = 0.7
ValRatio =  0.2
TestRatio = 0.1