Expressive Optimal Temporal Planning via Optimization Modulo Theory

Temporal Planning is the problem of synthesizing a course actions given predictive model system subject to temporal constraints. This kind planning finds natural applications in automation industrial processes and robotics when timing deadlines are important. Finding any plan often not enough as it sometimes needed optimize certain objective function: particularly interesting minimization makespan optimization costs actions. Despite importance problem, only few works literature tackled optimal because complicated intermix scheduling. In this paper, we address for very expressive class problems using reduction bounded Optimization Modulo Theory (OMT) powerful discrete/continuous framework. We theoretically empirically show power approach set baseline future research area.