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

SaveObjective = false

TimeStep = 5 # Overrides TimeStep in coverge_control_params.toml

SaveRobotWorldLocalMaps = false

CNNMapSize = 32

SaveAsSparseQ = true

NormalizeQ = true

[DataSetSplit]

TrainRatio = 0.7

ValRatio = 0.2

TestRatio = 0.1