The SPA Ontology: Towards a Web of Things Ready for Robotic Agents

We present the Simple Planning Annotation (spa) ontology for modeling preconditions and effects of interaction affordances within Web of Things Thing Descriptions and propose a mapping to the Planning Domain Definition Language to enable robot-device interaction. We use encoded semantic knowledge to generate a planning problem that can be used within existing AI planning algorithms to dynamically plan interaction sequences to achieve specified goals without the extensive pre-programming traditionally required, as demonstrated by the validation of our approach through a prototypical implementation. The scalability evaluation shows that when the number of input Web of Things actions increases by a factor of 1, 000, the runtime of the implemented prototype increases by about 14.3% and the memory consumption by about 9.4%, indicating vertical scalability.