SpaTiaL: Monitoring and Planning of Robotic Tasks Using Spatio-Temporal Logic Specifications

Abstract

Abstract Many tasks require robots to manipulate objects while satisfying a complex interplay of spatial and temporal constraints. For instance, a table setting robot first needs to place a mug and then fill it with coffee, while satisfying spatial relations such as forks need to placed left of plates. Existing solutions are often not robot-agnostic, not expressive enough to monitor and plan complex tasks, and require users to manually define object relations. We propose the spatio-temporal framework SpaTiaL that unifies the specification, monitoring, and planning of object-centric robotic tasks. SpaTiaL captures diverse spatial relations between objects and temporal task patterns. Our experiments with recorded data, simulations, and robots demonstrate how SpaTiaL provides real-time monitoring and facilitates online planning. SpaTiaL is open source and easily expandable to new object relations and robotic applications.