Temporal logic control for stochastic linear systems using abstraction refinement of probabilistic games

Svoreňová, Mária; Křetínský, Jan; Chmelík, Martin; Chatterjee, Krishnendu; Černá, Ivana; Belta, Călin

doi:10.1145/2728606.2728608

Cited by 26 publications

(32 citation statements)

References 27 publications

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“…There is a large body of results on automata theoretic approaches for controller synthesis [1], [16], [18], [23], [25]. The approach here is to construct a finite abstraction of the dynamical system and then invoke the LTL synthesis algorithms such as the one in [5].…”

Section: Related Workmentioning

confidence: 99%

Controller synthesis with inductive proofs for piecewise linear systems: An SMT-based algorithm

Huang

Wang

Mitra

et al. 2015

2015 54th IEEE Conference on Decision and Control (CDC)

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Abstract-We present a controller synthesis algorithm for reach-avoid problems for piecewise linear discrete-time systems. Our algorithm relies on SMT solvers and in this paper we focus on piecewise constant control strategies. Our algorithm generates feedback control laws together with inductive proofs of unbounded time safety and progress properties with respect to the reach-avoid sets. Under a reasonable robustness assumption, the algorithm is shown to be complete. That is, it either generates a controller of the above type along with a proof of correctness, or it establishes the impossibility of the existence of such controllers. To achieve this, the algorithm iteratively attempts to solve a weakened and strengthened versions of the SMT encoding of the reach-avoid problem. We present preliminary experimental results on applying this algorithm based on a prototype implementation.

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Section: Related Workmentioning

confidence: 99%

Controller synthesis with inductive proofs for piecewise linear systems: An SMT-based algorithm

Huang

Wang

Mitra

et al. 2015

2015 54th IEEE Conference on Decision and Control (CDC)

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“…[29,32], and stochastic games, e.g. [8,31] have been used in conjunction with temporal logic for controller synthesis of autonomous agents.…”

Section: Introductionmentioning

confidence: 99%

Strategy Synthesis for Autonomous Agents Using PRISM

Giaquinta

Hoffmann

Ireland

et al. 2018

Lecture Notes in Computer Science

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Abstract. We present probabilistic models for autonomous agent search and retrieve missions derived from Simulink models for an Unmanned Aerial Vehicle (UAV) and show how probabilistic model checking and the probabilistic model checker PRISM can be used for optimal controller generation. We introduce a sequence of scenarios relevant to UAVs and other autonomous agents such as underwater and ground vehicles. For each scenario we demonstrate how it can be modelled using the PRISM language, give model checking statistics and present the synthesised optimal controllers. We conclude with a discussion of the limitations when using probabilistic model checking and PRISM in this context and what steps can be taken to overcome them. In addition, we consider how the controllers can be returned to the UAV and adapted for use on larger search areas.

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“…Motion planning based on high-level temporal specifications has become an important area of research. Several methods have been developed for single robots, e.g., [5,15,18,22]; and for multiple robots, e.g., [2,6,19]. The multi-robot path planning problem with linear temporal logic (LTL) specifications can be categorised into two areas depending on the final goal: (i) each robot has its own task, or (ii) all the robots act as a team trying to accomplish a global specification.…”

Section: Introductionmentioning

confidence: 99%

Sampling-Based Path Planning for Multi-robot Systems with Co-Safe Linear Temporal Logic Specifications

Montana

Liu

Dodd

2017

Lecture Notes in Computer Science

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This paper addresses the problem of path planning for multiple robots under high-level specifications given as syntactically co-safe linear temporal logic formulae. Most of the existing solutions use the notion of abstraction to obtain a discrete transition system that simulates the dynamics of the robot. Nevertheless, these solutions have poor scalability with the dimension of the configuration space of the robots. For problems with a single robot, sampling-based methods have been presented as a solution to alleviate this limitation. The proposed solution extends the idea of sampling methods to the multiple robot case. The method samples the configuration space of the robots to incrementally constructs a transition system that models the motion of all the robots as a group. This transition system is then combined with a Büchi automaton, representing the specification, in a Cartesian product. The product is updated with each expansion of the transition system until a solution is found. We also present a new algorithm that improves the performance of the proposed method by guiding the expansion of the transition system. The method is demonstrated with examples considering different number of robots and specifications.

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Temporal logic control for stochastic linear systems using abstraction refinement of probabilistic games

Cited by 26 publications

References 27 publications

Controller synthesis with inductive proofs for piecewise linear systems: An SMT-based algorithm

Controller synthesis with inductive proofs for piecewise linear systems: An SMT-based algorithm

Strategy Synthesis for Autonomous Agents Using PRISM

Sampling-Based Path Planning for Multi-robot Systems with Co-Safe Linear Temporal Logic Specifications

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