The increasing demand for data to train Neural Networks and other AI models is driving the development of techniques that enable programmers to acquire new data in a faster, cheaper, and easier way. This thesis focuses on creating a synthetic dataset using NVIDIA Isaac Sim, an application built on NVIDIA Omniverse, which facilitates the creation of a photorealistic "digital twin" of a specific environment and the randomization of its elements. Synthetic data is a class of data artificially generated, coming from the digital world rather than real world, with the main advantage of having almost unlimited amount of data, already labelled, that can deliberately include rare but crucial corner cases, or, in other cases, overcome the problem of not having data for that specific task.