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  • This paper studies the problem of control strategy synthesis for dynamical systems with differential constraints to fulfill a given reachability goal specification while satisfying a set of safety rules. Particular attention is devoted to goals that become feasible only if a subset of the safety rules are violated. The proposed algorithm computes a control law, that minimizes the level of unsafety while the desired goal is guaranteed to be reached. This problem is motivated by an autonomous car navigating an urban environment while following rules of the road such as %22always travel in right lane%22 and %22do not change lanes frequently%22. Ideas behind sampling based motion-planning algorithms, such as Probabilistic Road Maps (PRMs) and Rapidly-exploring Random Trees (RRTs), are employed to incrementally construct a finite concretization of the dynamics as a durational Kripke structure.
  • This paper studies the problem of control strategy synthesis for dynamical systems with differential constraints to fulfill a given reachability goal specification while satisfying a set of safety rules. Particular attention is devoted to goals that become feasible only if a subset of the safety rules are violated. The proposed algorithm computes a control law, that minimizes the level of unsafety while the desired goal is guaranteed to be reached. This problem is motivated by an autonomous car navigating an urban environment while following rules of the road such as %22always travel in right lane%22 and %22do not change lanes frequently%22. Ideas behind sampling based motion-planning algorithms, such as Probabilistic Road Maps (PRMs) and Rapidly-exploring Random Trees (RRTs), are employed to incrementally construct a finite concretization of the dynamics as a durational Kripke structure. (en)
Title
  • Incremental Sampling-Based Algorithm for Minimum-Violation Motion Planning
  • Incremental Sampling-Based Algorithm for Minimum-Violation Motion Planning (en)
skos:prefLabel
  • Incremental Sampling-Based Algorithm for Minimum-Violation Motion Planning
  • Incremental Sampling-Based Algorithm for Minimum-Violation Motion Planning (en)
skos:notation
  • RIV/00216224:14330/13:00071895!RIV14-MSM-14330___
http://linked.open...avai/predkladatel
http://linked.open...avai/riv/aktivita
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  • P(LH11065)
http://linked.open...vai/riv/dodaniDat
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  • 79512
http://linked.open...ai/riv/idVysledku
  • RIV/00216224:14330/13:00071895
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  • motion planning; temporal logic; sampling-based planning; formal methods (en)
http://linked.open.../riv/klicoveSlovo
http://linked.open...ontrolniKodProRIV
  • [B54E2C94FAA8]
http://linked.open...v/mistoKonaniAkce
  • Florence, Italy
http://linked.open...i/riv/mistoVydani
  • Florence, Italy
http://linked.open...i/riv/nazevZdroje
  • Proceedings of the IEEE 52nd Annual Conference on Decision and Control (CDC), 2013
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  • Rus, Daniela
  • Tůmová, Jana
  • Chaudhari, Pratik
  • Frazzoli, Emilio
  • Karaman, Sertac
  • Reyes Castro, Luis Ignacio
http://linked.open...vavai/riv/typAkce
http://linked.open.../riv/zahajeniAkce
number of pages
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  • IEEE
https://schema.org/isbn
  • 9781467357166
http://localhost/t...ganizacniJednotka
  • 14330
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