# Sequence Planner: A Framework for Control of Intelligent Automation Systems
## 2 The Sequence Planner Control Framework
### Operation Planner
The focus in SP is to assume control of the internal state machines of the individual resources. This allows the complex task of coordinating many resources to be handled by the transition planner, even though there are complex interdependencies between resources. Resources can be made highly reusable by applying the proposed combination of resource specifications and operations as the main modeling concept. Achieving a good result, however, requires that the modeling task be performed to a high standard. Modeling errors _will_ be found and used as loop-holes by the transition planner. The requirements of a well-modeled system indicate that there need to be guarantees about what can and cannot happen. Writing, testing, and then trusting the written specifications make formal verification and virtual validation crucial tools during development. We have found that the operations as defined in SP are a natural way to define a hierachical model, in contrast to PPDL-based planning systems such as ROSPlan, where Hierarchical Task Networks (HTNs) [33] need to be defined. However, due to the differences in modeling language, no direct comparison has yet been made between the two difference systems. Naturally, a system that relies on formal methods and online planning has an upper limit to the complexity of the model. State space explosion is an issue, both for verification and for efficient planning. As we can observe in Section 4, Planning times go up to around 1-2 s for the longer plans. This implies that the proposed framework cannot handle much larger systems than presented in Section 3. However, as long as the complexity of a single station is not too high, the framework should be applicable. Additionally, new state-of-the-art planners and model checkers can be utilized to increase the raw performance. Future work will involve learning a distribution of the duration of the operations (which naturally fluctuate depending on the state of the resources), which can be used by the operation planner to find time-optimal plans. Additionally, an investigation should be made on how the operation planner can take into account non-deterministic effects. This could reduce the need for replanning and allow more time to instead be spent computing a high-quality plan. Sequence Planner is open source software and can be found at [[http://github.com/sequenceplanner/sp](http://github.com/sequenceplanner/sp)]([http://github.com/sequenceplanner/sp](http://github.com/sequenceplanner/sp)) (accessed on 24 May 2022). Conceptualization, M.D., E.E., K.B. and P.F. ; methodology, M.D., E.E., K.B. and P.F. ; software, M.D., E.E. and K.B. ; writing--original draft preparation, M.D. ; writing--reviewand editing, K.B., M.F. and P.F. ; supervision, K.B., M.F. and P.F. All authors have read and agreed to the published version of the manuscript. This work has been supported by UNIFICATION, Vinnova, Produktion 2030 and UNICORN, Vinnova, Effektiva och uppkopplade transportsystem. The Sequence Planner software has been supported by ROSIN--ROS-Industrial Quality-Assured Robot Software Components, European Union's Horizon 2020 grant agreement No. 732287. Not applicable. The authors declare no conflict of interest. ## References

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