GENERATING SYNTHETIC TRAINING DATA FOR PERCEPTION MACHINE LEARNING MODELS USING SIMULATED ENVIRONMENTS

A method for training a machine learning model is provided. The method includes generating a set of candidate training data based on a simulated environment and a first set of environmental parameters. The method also includes training a machine learning model based on the set of candidate training data. The method further includes obtaining a set of segmentations based on the machine learning model and a set of test data. The method further includes determining whether a mean intersection-over-union, MIOU, of the set of segmentations has increased by more than a threshold change. The method further includes generating a next set of candidate training data based on the simulated environment and a second set of environmental parameters for the simulated environment, in response to determining that the MIOU has increased by more than the threshold MIOU amount.