14,146 research outputs found
Abstractions and sensor design in partial-information, reactive controller synthesis
Automated synthesis of reactive control protocols from temporal logic
specifications has recently attracted considerable attention in various
applications in, for example, robotic motion planning, network management, and
hardware design. An implicit and often unrealistic assumption in this past work
is the availability of complete and precise sensing information during the
execution of the controllers. In this paper, we use an abstraction procedure
for systems with partial observation and propose a formalism to investigate
effects of limitations in sensing. The abstraction procedure enables the
existing synthesis methods with partial observation to be applicable and
efficient for systems with infinite (or finite but large number of) states.
This formalism enables us to systematically discover sensing modalities
necessary in order to render the underlying synthesis problems feasible. We use
counterexamples, which witness unrealizability potentially due to the
limitations in sensing and the coarseness in the abstract system, and
interpolation-based techniques to refine the model and the sensing modalities,
i.e., to identify new sensors to be included, in such synthesis problems. We
demonstrate the method on examples from robotic motion planning.Comment: 9 pages, 4 figures, Accepted at American Control Conference 201
A multi-paradigm language for reactive synthesis
This paper proposes a language for describing reactive synthesis problems
that integrates imperative and declarative elements. The semantics is defined
in terms of two-player turn-based infinite games with full information.
Currently, synthesis tools accept linear temporal logic (LTL) as input, but
this description is less structured and does not facilitate the expression of
sequential constraints. This motivates the use of a structured programming
language to specify synthesis problems. Transition systems and guarded commands
serve as imperative constructs, expressed in a syntax based on that of the
modeling language Promela. The syntax allows defining which player controls
data and control flow, and separating a program into assumptions and
guarantees. These notions are necessary for input to game solvers. The
integration of imperative and declarative paradigms allows using the paradigm
that is most appropriate for expressing each requirement. The declarative part
is expressed in the LTL fragment of generalized reactivity(1), which admits
efficient synthesis algorithms, extended with past LTL. The implementation
translates Promela to input for the Slugs synthesizer and is written in Python.
The AMBA AHB bus case study is revisited and synthesized efficiently,
identifying the need to reorder binary decision diagrams during strategy
construction, in order to prevent the exponential blowup observed in previous
work.Comment: In Proceedings SYNT 2015, arXiv:1602.0078
Strategy Synthesis for Autonomous Agents Using PRISM
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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