Corpus ID: 16015233

Control with Probabilistic Signal Temporal Logic

@article{Yoo2015ControlWP,
  title={Control with Probabilistic Signal Temporal Logic},
  author={Chanyeol Yoo and Calin Belta},
  journal={ArXiv},
  year={2015},
  volume={abs/1510.08474}
}
Autonomous agents often operate in uncertain environments where their decisions are made based on beliefs over states of targets. We are interested in controller synthesis for complex tasks defined over belief spaces. Designing such controllers is challenging due to computational complexity and the lack of expressivity of existing specification languages. In this paper, we propose a probabilistic extension to signal temporal logic (STL) that expresses tasks over continuous belief spaces. We… Expand
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References

SHOWING 1-10 OF 31 REFERENCES
Temporal Logic Motion Planning and Control With Probabilistic Satisfaction Guarantees
We describe a computational framework for automatic deployment of a robot with sensor and actuator noise from a temporal logic specification over a set of properties that are satisfied by the regionsExpand
Temporal logic control in dynamic environments with probabilistic satisfaction guarantees
TLDR
This work derives a solution to the automatic deployment of a robot from a temporal logic specification assuming three different levels of knowledge and sensing capabilities of the robot, and describes an optimal solution in one setting and sub-optimal, reactive solutions in the other two. Expand
LTL Control in Uncertain Environments with Probabilistic Satisfaction Guarantees
TLDR
The problem of generating a control policy for a Markov Decision Process (MDP) such that the probability of satisfying an LTL formula over its states is maximized can be reduced to the problem of creating a robot control strategy that maximizes the probability to accomplish a task. Expand
Distributed Multi-Agent Persistent Surveillance Under Temporal Logic Constraints∗
TLDR
This work forms a distributed optimization problem, where each agent plans its trajectory based only on local information and uses a formal methods approach to show that any trajectory resulting from the proposed controller satisfies the corresponding TL constraints. Expand
Temporal logic robot control based on automata learning of environmental dynamics
TLDR
A technique to automatically generate a control policy for a robot moving in an environment that includes elements with unknown, randomly changing behavior, and it is shown that the obtained control policy converges to an optimal one when the partially unknown behavior patterns are fully learned. Expand
Probabilistic Temporal Logic for Motion Planning with Resource Threshold Constraints
TLDR
This work proposes an extension to probabilistic computation tree logic that expresses real-valued resource threshold constraints, and presents model-checking algorithms that evaluate a piecewise control policy with respect to a formal specification and hard or soft performance guarantees. Expand
Efficient reactive controller synthesis for a fragment of linear temporal logic
TLDR
A fragment of linear temporal logic is introduced that can be used to specify common motion planning tasks such as safe navigation, response to the environment, persistent coverage, and surveillance. Expand
Receding horizon temporal logic planning for dynamical systems
  • T. Wongpiromsarn, U. Topcu, R. Murray
  • Computer Science
  • Proceedings of the 48h IEEE Conference on Decision and Control (CDC) held jointly with 2009 28th Chinese Control Conference
  • 2009
TLDR
To address the computational difficulties in the synthesis of a discrete planner, this paper presents a receding horizon based scheme for executing finite state automata that essentially reduces the synthesis problem to a set of smaller problems. Expand
Provably-correct stochastic motion planning with safety constraints
TLDR
Novel algorithms for model checking and policy synthesis in PCTL are proposed that provide a quantitative measure of safety and completion time for a given policy, and synthesise policies that minimise completion time with respect to a given safety threshold. Expand
Receding horizon surveillance with temporal logic specifications
TLDR
This paper provides a framework which guarantees that the overall trajectory of the system satisfies the desired linear temporal logic specification, while the control decisions are made based on local information obtained in real time. Expand
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