A summer research internship working with UCL professors to verify and further the application of deep neural networks in trajectory optimisation. I will be replicating a brand new optimization method that learns an infinite set of solutions in trajectory optimization by learning a solution manifold from which the user can select a preferred solution through a continuous latent representation. Once this method is verified, I aim to add the ability to generate both continuous and discrete latent variables, and assess this method's future potential in unseen situations, eliminating the need to retrain the model in each new optimisation problem.