mlsanityData to 7 Oct 2026

A Smooth Robustness Measure of Signal Temporal Logic for Symbolic Control

arXiv 2006.05239 ↗First posted 9 Jun 2020eess.SY cs.RO cs.SYcited by 21

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Abstract (arXiv)

Recent years have seen an increasing use of Signal Temporal Logic (STL) as a formal specification language for symbolic control, due to its expressiveness and closeness to natural language. Furthermore, STL specifications can be encoded as cost functions using STL's robust semantics, transforming the synthesis problem into an optimization problem. Unfortunately, these cost functions are non-smooth and non-convex, and exact solutions using mixed-integer programming do not scale well. Recent work has focused on using smooth approximations of robustness, which enable faster gradient-based methods to find local maxima, at the expense of soundness and/or completeness. We propose a novel robustness approximation that is smooth everywhere, sound, and asymptotically complete. Our approach combines the benefits of existing approximations, while enabling an explicit tradeoff between conservativeness and completeness.

Key facts. Cited by 21 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Jun 2020.

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Citing papers per year: 2021: 4; 2022: 3; 2023: 3; 2024: 3; 2025: 2; 2026: 6.

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  1. 2024A Survey of Optimization-based Task and Motion Planning: From Classical To Learning Approachescited by 19
  2. 2023Learning Robust and Correct Controllers from Signal Temporal Logic Specifications Using BarrierNetcited by 6
  3. 2025Zero-Shot Trajectory Planning for Signal Temporal Logic Taskscited by 6
  4. 2022Interpretable Fault Diagnosis of Rolling Element Bearings with Temporal Logic Neural Networkcited by 4
  5. 2021Safe Model-based Control from Signal Temporal Logic Specifications Using Recurrent Neural Networkscited by 3
  6. 2022Model Predictive Robustness of Signal Temporal Logic Predicatescited by 3
  7. 2023Requirement falsification for cyber-physical systems using generative modelscited by 3
  8. 2021Neural Network-based Control for Multi-Agent Systems from Spatio-Temporal Specificationscited by 2
  9. 2021Reinforcement Learning with Formal Performance Metrics for Quadcopter Attitude Control under Non-nominal Contextscited by 2
  10. 2024Interpretable Imitation Learning via Generative Adversarial STL Inference and Controlcited by 2
  11. 2026ClarifySTL: An Interactive LLM Agent Framework for STL Transformation through Requirements Clarificationcited by 2
  12. 2023Co-learning Planning and Control Policies Constrained by Differentiable Logic Specificationscited by 1
9 more
  1. 2026Spatiotemporal Robustness of Temporal Logic Tasks using Multi-Objective Reasoningcited by 1
  2. 2021Reinforcement Learning Agent Training with Goals for Real World Taskscited by 0
  3. 2022CatlNet: Learning Communication and Coordination Policies from CaTL+ Specificationscited by 0
  4. 2024Scaling Learning based Policy Optimization for Temporal Logic Tasks by Controller Network Dropoutcited by 0
  5. 2025Feasibility-aware Learning of Robust Temporal Logic Controllers using BarrierNetcited by 0
  6. 2026Zero-Shot Signal Temporal Logic Planning with Disjunctive Branch Selection in Dynamic Semantic Mapscited by 0
  7. 2026Reward Machines for Signal Temporal Logiccited by 0
  8. 2026Backward through Time, Algebraicallycited by 0
  9. 2026From LLM-Generated Specifications to Learned Quadruped Locomotioncited by 0