TuLiP

TuLiP: a software toolbox for receding horizon temporal logic planning. This paper describes TuLiP, a Python-based software toolbox for the synthesis of embedded control software that is provably correct with respect to an expressive subset of linear temporal logic (LTL) specifications. TuLiP combines routines for (1) finite state abstraction of control systems, (2) digital design synthesis from LTL specifications, and (3) receding horizon planning. The underlying digital design synthesis routine treats the environment as adversary; hence, the resulting controller is guaranteed to be correct for any admissible environment profile. TuLiP applies the receding horizon framework, allowing the synthesis problem to be broken into a set of smaller problems, and consequently alleviating the computational complexity of the synthesis procedure, while preserving the correctness guarantee.


References in zbMATH (referenced in 13 articles )

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  1. Amram, Gal; Maoz, Shahar; Pistiner, Or: GR(1)*: GR(1) specifications extended with existential guarantees (2021)
  2. Mohajerani, Sahar; Malik, Robi; Wintenberg, Andrew; Lafortune, Stéphane; Ozay, Necmiye: Divergent stutter bisimulation abstraction for controller synthesis with linear temporal logic specifications (2021)
  3. Apaza-Perez, W. Alejandro; Combastel, Christophe; Zolghadri, Ali: On distributed symbolic control of interconnected systems under persistency specifications (2020)
  4. Fan, Chuchu; Miller, Kristina; Mitra, Sayan: Fast and guaranteed safe controller synthesis for nonlinear vehicle models (2020)
  5. Hashimoto, Kazumune; Dimarogonas, Dimos V.: Resource-aware networked control systems under temporal logic specifications (2019)
  6. Khaled, Mahmoud; Zamani, Majid: \textsfpFaces: an acceleration ecosystem for symbolic control (2019)
  7. Bart, Anicet; Delahaye, Benoît; Fournier, Paulin; Lime, Didier; Monfroy, Éric; Truchet, Charlotte: Reachability in parametric interval Markov chains using constraints (2018)
  8. Li, Yinan; Liu, Jun: ROCS: a robustly complete control synthesis tool for nonlinear dynamical systems (2018)
  9. Nilsson, Petter; Ozay, Necmiye; Liu, Jun: Augmented finite transition systems as abstractions for control synthesis (2017)
  10. Schmuck, Anne-Kathrin; Majumdar, Rupak; Leva, Adrian: Dynamic hierarchical reactive controller synthesis (2017)
  11. Liu, Jun; Ozay, Necmiye: Finite abstractions with robustness margins for temporal logic-based control synthesis (2016)
  12. Rungger, Matthias; Zamani, Majid: SCOTS: a tool for the synthesis of symbolic controllers (2016)
  13. Svoreňová, Mária; Kwiatkowska, Marta: Quantitative verification and strategy synthesis for stochastic games (2016)