Current artificial intelligence (AI) methods for planning and scheduling (P&S), whether model-based or data-driven, do not inspire enough confidence to be massively adopted and achieve their potential impact. The EU-funded TUPLES project will contribute to an integrated and human-centred approach for the development of P&S tools in order to increase confidence and adoption. Overall, it has three goals. Firstly, to develop hybrid P&S methods that combine the efficiency, flexibility, and adaptability of data-driven learning approaches with the robustness, reliability, and clarity of model-based reasoning methods. Secondly, designing methods for verifying and explaining the solutions produced by P&S systems. Lastly, conducting case studies, from aeroplane pilot assistance to soccer team management and waste collection.