@article{Micheli_Scala_2019, title={Temporal Planning with Temporal Metric Trajectory Constraints}, volume={33}, url={https://ojs.aaai.org/index.php/AAAI/article/view/4762}, DOI={10.1609/aaai.v33i01.33017675}, abstractNote={<p>In several industrial applications of planning, complex temporal metric trajectory constraints are needed to adequately model the problem at hand. For example, in production plants, items must be processed following a “recipe” of steps subject to precise timing constraints. Modeling such domains is very challenging in existing action-based languages due to the lack of sufficiently expressive trajectory constraints.</p><p>We propose a novel temporal planning formalism allowing quantified temporal constraints over execution timing of action instances. We build on top of instantaneous actions borrowed from classical planning and add expressive temporal constructs. The paper details the semantics of our new formalism and presents a solving technique grounded in classical, heuristic forward search planning. Our experiments prove the proposed framework superior to alternative state-of-theart planning approaches on industrial benchmarks, and competitive with similar solving methods on well known benchmarks took from the planning competition.</p>}, number={01}, journal={Proceedings of the AAAI Conference on Artificial Intelligence}, author={Micheli, Andrea and Scala, Enrico}, year={2019}, month={Jul.}, pages={7675-7682} }