914 research outputs found
Efficient Automata-based Planning and Control under Spatio-Temporal Logic Specifications
The use of spatio-temporal logics in control is motivated by the need to
impose complex spatial and temporal behavior on dynamical systems, and to
control these systems accordingly. Synthesizing correct-by-design control laws
is a challenging task resulting in computationally demanding methods. We
consider efficient automata-based planning for continuous-time systems under
signal interval temporal logic specifications, an expressive fragment of signal
temporal logic. The planning is based on recent results for automata-based
verification of metric interval temporal logic. A timed signal transducer is
obtained accepting all Boolean signals that satisfy a metric interval temporal
logic specification, which is abstracted from the signal interval temporal
logic specification at hand. This transducer is modified to account for the
spatial properties of the signal interval temporal logic specification,
characterizing all real-valued signals that satisfy this specification. Using
logic-based feedback control laws, such as the ones we have presented in
earlier works, we then provide an abstraction of the system that, in a suitable
way, aligns with the modified timed signal transducer. This allows to avoid the
state space explosion that is typically induced by forming a product automaton
between an abstraction of the system and the specification.Comment: 8 pages - Accepted for Publication at ACC 202
Robotic swarm control from spatio-temporal specifications
In this paper, we study the problem of controlling a two-dimensional robotic swarm with the purpose of achieving high level and complex spatio-temporal patterns. We use a rich spatio-temporal logic that is capable of describing a wide range of time varying and complex spatial configurations, and develop a method to encode such formal specifications as a set of mixed integer linear constraints, which are incorporated into a mixed integer linear programming problem. We plan trajectories for each individual robot such that the whole swarm satisfies the spatio-temporal requirements, while optimizing total robot movement and/or a metric that shows how strongly the swarm trajectory resembles given spatio-temporal behaviors. An illustrative case study is included.This work was partially supported by the National Science Foundation under grants NRI-1426907 and CMMI-1400167. (NRI-1426907 - National Science Foundation; CMMI-1400167 - National Science Foundation
Towards Cancer Hybrid Automata
This paper introduces Cancer Hybrid Automata (CHAs), a formalism to model the
progression of cancers through discrete phenotypes. The classification of
cancer progression using discrete states like stages and hallmarks has become
common in the biology literature, but primarily as an organizing principle, and
not as an executable formalism. The precise computational model developed here
aims to exploit this untapped potential, namely, through automatic verification
of progression models (e.g., consistency, causal connections, etc.),
classification of unreachable or unstable states and computer-generated
(individualized or universal) therapy plans. The paper builds on a
phenomenological approach, and as such does not need to assume a model for the
biochemistry of the underlying natural progression. Rather, it abstractly
models transition timings between states as well as the effects of drugs and
clinical tests, and thus allows formalization of temporal statements about the
progression as well as notions of timed therapies. The model proposed here is
ultimately based on hybrid automata, and we show how existing controller
synthesis algorithms can be generalized to CHA models, so that therapies can be
generated automatically. Throughout this paper we use cancer hallmarks to
represent the discrete states through which cancer progresses, but other
notions of discretely or continuously varying state formalisms could also be
used to derive similar therapies.Comment: In Proceedings HSB 2012, arXiv:1208.315
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