The employment of intralogistic robots in warehouses has become increasingly prevalent due to technological advancements; in fact, they enable more efficient logistic operations, increasing productivity and cost-effectiveness. The research community is showing a keen interest in the subject and directing its attention towards the implementation of risk-aware robots with planning capabilities. Nevertheless, to our knowledge, no one has yet investigated the application of the Dynamic Programming paradigm for the scheduling of tasks for intralogistic robots. Therefore, this dissertation focuses on addressing this topic, proposing various resolution methods for a stochastic dynamic scheduling problem, based on Dynamic Programming and its approximated versions.