Automated Testing with Temporal Logic Specifications for Robotic Controllers using Adaptive Experiment Design
@article{Innes2021AutomatedTW, title={Automated Testing with Temporal Logic Specifications for Robotic Controllers using Adaptive Experiment Design}, author={Craig Innes and Subramanian Ramamoorthy}, journal={ArXiv}, year={2021}, volume={abs/2109.08071} }
Many robot control scenarios involve assessing system robustness against a task specification. If either the controller or environment are composed of “black-box” components with unknown dynamics, we cannot rely on formal verification to assess our system. Assessing robustness via exhaustive testing is also often infeasible if the number of possible environments is large compared to experiment cost. Given limited budget, we provide a method to choose experiment inputs which accurately reflect…
References
SHOWING 1-10 OF 46 REFERENCES
Robust control for signal temporal logic specifications using discrete average space robustness
- Computer ScienceAutom.
- 2019
Smooth operator: Control using the smooth robustness of temporal logic
- Computer Science2017 IEEE Conference on Control Technology and Applications (CCTA)
- 2017
This work formalizes the requirements as formulas in Metric Temporal Logic (MTL), and designs a controller that maximizes the robustness of the MTL formula, thus enabling the use of powerful gradient descent optimizers.
DryVR: Data-Driven Verification and Compositional Reasoning for Automotive Systems
- Computer ScienceCAV
- 2017
The DryVR framework is presented, which includes a probabilistic algorithm for learning sensitivity of the continuous trajectories from simulation data, a bounded reachability analysis algorithm that uses the learned sensitivity, and reasoning techniques based on simulation relations and sequential composition that enable verification of complex systems under long switching sequences.
Locally optimal reach set over-approximation for nonlinear systems
- Computer Science2016 International Conference on Embedded Software (EMSOFT)
- 2016
New techniques to compute a locally optimal bloating factor based on discrepancy functions, which allow construction of reach set over-approximations from simulation traces for general nonlinear systems.
Specification Patterns for Robotic Missions
- Computer ScienceIEEE Transactions on Software Engineering
- 2021
A catalog of 22 mission specification patterns for mobile robots, together with tooling for instantiating, composing, and compiling the patterns to create mission specifications, which provide solutions for recurrent specification problems.
Robust Satisfaction of Temporal Logic over Real-Valued Signals
- MathematicsFORMATS
- 2010
We consider temporal logic formulae specifying constraints in continuous time and space on the behaviors of continuous and hybrid dynamical system admitting uncertain parameters. We present several…
Model-based reinforcement learning for approximate optimal control with temporal logic specifications
- Computer Science, MathematicsHSCC
- 2021
This paper forms a sequence of reach-avoid optimal control sub-problems and takes a learning-based approach to approximately solve this sequence of optimal control problems online without requiring full knowledge of the system dynamics.
Simulation-based Adversarial Test Generation for Autonomous Vehicles with Machine Learning Components
- Computer Science2018 IEEE Intelligent Vehicles Symposium (IV)
- 2018
This work presents a testing framework that is compatible with test case generation and automatic falsification methods, which are used to evaluate cyber-physical systems and can be used to increase the reliability of autonomous driving systems.
A Novel Hybrid Sequential Design Strategy for Global Surrogate Modeling of Computer Experiments
- Computer ScienceSIAM J. Sci. Comput.
- 2011
A novel hybrid sequential design strategy is proposed which uses a Monte Carlo-based approximation of a Voronoi tessellation for exploration and local linear approximations of the simulator for exploitation, and can be used in heterogeneous modeling environments, where multiple model types are used at the same time.
Compositional Falsification of Cyber-Physical Systems with Machine Learning Components
- Computer ScienceNFM
- 2017
A compositional falsification framework where a temporal logic falsifier and a machine learning analyzer cooperate with the aim of finding falsifying executions of the considered model to address the problem of falsifying signal temporal logic specifications for CPS with ML components.