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Mission Planning for Multiple Vehicles with Temporal Specifications using UxAS.

, , , and . ADHS, volume 51 of IFAC-PapersOnLine, page 67-72. Elsevier, (2018)

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Simulation-based Adversarial Test Generation for Autonomous Vehicles with Machine Learning Components., , , and . Intelligent Vehicles Symposium, page 1555-1562. IEEE, (2018)Gray-box adversarial testing for control systems with machine learning components., and . HSCC, page 179-184. ACM, (2019)Worst-case Satisfaction of STL Specifications Using Feedforward Neural Network Controllers: A Lagrange Multipliers Approach., and . ACM Trans. Embedded Comput. Syst., 18 (5s): 107:1-107:20 (2019)Rapidly-exploring Random Trees-based Test Generation for Autonomous Vehicles., and . CoRR, (2019)Gray-box Adversarial Testing for Control Systems with Machine Learning Component., and . CoRR, (2018)Towards modeling and analysis of cyber-physical medical systems., , , and . ISABEL, page 154:1-154:5. ACM, (2011)Evaluating Perception Systems for Autonomous Vehicles Using Quality Temporal Logic., , , and . RV, volume 11237 of Lecture Notes in Computer Science, page 409-416. Springer, (2018)Mission Planning for Multiple Vehicles with Temporal Specifications using UxAS., , , and . ADHS, volume 51 of IFAC-PapersOnLine, page 67-72. Elsevier, (2018)Embedded software for robotics: challenges and future directions: special session., , , , , , , and . EMSOFT, page 10. IEEE, (2018)Local Descent for Temporal Logic Falsification of Cyber-Physical Systems., and . CyPhy, volume 11267 of Lecture Notes in Computer Science, page 11-26. Springer, (2017)